AI/DS and its applications in medicine/cardiovascular disease/breast cancer
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Marafino BJ, Escobar GJ, Baiocchi MT, Liu VX, Plimier CC, Schuler A. Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: observational study. bmj. 2021 Aug 11;374. link
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Kamran F, Tang S, Otles E, McEvoy DS, Saleh SN, Gong J, Li BY, Dutta S, Liu X, Medford RJ, Valley TS. Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study. bmj. 2022 Feb 17;376. link
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Others
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AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Dennis JM, Young KG, Cardoso P, Güdemann LM, McGovern AP, Farmer A, Holman RR, Sattar N, McKinley TJ, Pearson ER, Jones AG. A five-drug class model using routinely available clinical features to optimise prescribing in type 2 diabetes: a prediction model development and validation study. The Lancet. 2025 Mar 1;405(10480):701-14. link
Cavalcanti DM, de Sales LD, da Silva AF, Basterra EL, Pena D, Monti C, Barreix G, Silva NJ, Vaz P, Saute F, Fanjul G. Evaluating the impact of two decades of USAID interventions and projecting the effects of defunding on mortality up to 2030: a retrospective impact evaluation and forecasting analysis. The Lancet. 2025 Jun 30. link
Chan K, Wahome E, Tsiachristas A, Antonopoulos AS, Patel P, Lyasheva M, Kingham L, West H, Oikonomou EK, Volpe L, Mavrogiannis MC. Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study. The Lancet. 2024 May 29. link
Taylor C, Dodwell D, McGale P, Hills RK, Berry R, Bradley R, Braybrooke J, Clarke M, Gray R, Holt F, Liu Z. Radiotherapy to regional nodes in early breast cancer: an individual patient data meta-analysis of 14 324 women in 16 trials. The Lancet. 2023 Nov 25;402(10416):1991-2003. link
Forrest IS, Petrazzini BO, Duffy Á, Park JK, Marquez-Luna C, Jordan DM, Rocheleau G, Cho JH, Rosenson RS, Narula J, Nadkarni GN. Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts. The Lancet. 2023 Jan 21;401(10372):215-25. link
Ni X, Li Z, Li X, Zhang X, Bai G, Liu Y, Zheng R, Zhang Y, Xu X, Liu Y, Jia C. Socioeconomic inequalities in cancer incidence and access to health services among children and adolescents in China: a cross-sectional study. The Lancet. 2022 Sep 24;400(10357):1020-32. link
Karwath A, Bunting KV, Gill SK, Tica O, Pendleton S, Aziz F, Barsky AD, Chernbumroong S, Duan J, Mobley AR, Cardoso VR. Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis. The Lancet. 2021 Oct 16;398(10309):1427-35. link
D'Ascenzo F, De Filippo O, Gallone G, Mittone G, Deriu MA, Iannaccone M, Ariza-Solé A, Liebetrau C, Manzano-Fernández S, Quadri G, Kinnaird T. Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets. The Lancet. 2021 Jan 16;397(10270):199-207. link
Takahashi K, Serruys PW, Fuster V, Farkouh ME, Spertus JA, Cohen DJ, Park SJ, Park DW, Ahn JM, Kappetein AP, Head SJ. Redevelopment and validation of the SYNTAX score II to individualise decision making between percutaneous and surgical revascularisation in patients with complex coronary artery disease: secondary analysis of the multicentre randomised controlled SYNTAXES trial with external cohort validation. The Lancet. 2020 Oct 31;396(10260):1399-412. link
Attia ZI, Noseworthy PA, Lopez-Jimenez F, Asirvatham SJ, Deshmukh AJ, Gersh BJ, Carter RE, Yao X, Rabinstein AA, Erickson BJ, Kapa S. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction. The Lancet. 2019 Sep 7;394(10201):861-7. link
Chilamkurthy S, Ghosh R, Tanamala S, Biviji M, Campeau NG, Venugopal VK, Mahajan V, Rao P, Warier P. Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study. The Lancet. 2018 Dec 1;392(10162):2388-96. link
Others
Coles CE, Earl H, Anderson BO, Barrios CH, Bienz M, Bliss JM, Cameron DA, Cardoso F, Cui W, Francis PA, Jagsi R. The lancet breast cancer commission. The Lancet. 2024 May 11;403(10439):1895-950. link
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Marrazzo J, Neuzil K, Bertagnolli M. How the US National Institutes of Health is confronting health threats in a changing world. The Lancet. 2024 Dec 7;404(10469):2224-6. link
Sengupta PP, Kluin J, Lee SP, Oh JK, Smits AI. The future of valvular heart disease assessment and therapy. The Lancet. 2024 Apr 20;403(10436):1590-602. link
James ND, Tannock I, N'Dow J, Feng F, Gillessen S, Ali SA, Trujillo B, Al-Lazikani B, Attard G, Bray F, Compérat E. The Lancet Commission on prostate cancer: planning for the surge in cases. The Lancet. 2024 Apr 27;403(10437):1683-722. link
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Chen X, Giles J, Yao Y, Yip W, Meng Q, Berkman L, Chen H, Chen X, Feng J, Feng Z, Glinskaya E. The path to healthy ageing in China: a Peking University–Lancet Commission. The Lancet. 2022 Dec 3;400(10367):1967-2006. link
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Sun J, Feng T, Wang B, Li F, Han B, Chu M, Gong F, Yi Q, Zhou X, Chen S, Sun X. Leveraging artificial intelligence for predicting spontaneous closure of perimembranous ventricular septal defect in children: a multicentre, retrospective study in China. The Lancet Digital Health. 2025 Jan 1;7(1):e44-53. link
Marra C, Chico T, Alexandrow A, Dixon WG, Briffa N, Rainaldi E, Little MA, Size K, Tsanas A, Franklin JB, Kapur R. Addressing the challenges of integrating digital health technologies to measure patient-centred outcomes in clinical registries. The Lancet Digital Health. 2025 Mar 1;7(3):e225-31. link
Sau A, Sieliwonczyk E, Patlatzoglou K, Pastika L, McGurk KA, Ribeiro AH, Ribeiro AL, Ho JE, Peters NS, Ware JS, Tayal U. Artificial intelligence-enhanced electrocardiography for the identification of a sex-related cardiovascular risk continuum: a retrospective cohort study. The Lancet Digital Health. 2025 Mar 1;7(3):e184-94. link
Hernström V, Josefsson V, Sartor H, Schmidt D, Larsson AM, Hofvind S, Andersson I, Rosso A, Hagberg O, Lång K. Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study. The Lancet Digital Health. 2025 Feb 3. link
Kehayias CE, Bontempi D, Quirk S, Friesen S, Bredfeldt J, Kosak T, Kearney M, Tishler R, Pashtan I, Huynh MA, Aerts HJ. A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy. The Lancet Digital Health. 2025 Jan 1;7(1):e13-22. link
Cuartero CT, Carnegie AC, Cucunuba ZM, Cori A, Hollis SM, Van Gaalen RD, Baidjoe AY, Spina AF, Lees JA, Cauchemez S, Santos M. From the 100 Day Mission to 100 lines of software development: how to improve early outbreak analytics. The Lancet Digital Health. 2025 Feb 1;7(2):e161-6. link
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Oikonomou EK, Vaid A, Holste G, Coppi A, McNamara RL, Baloescu C, Krumholz HM, Wang Z, Apakama DJ, Nadkarni GN, Khera R. Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: A multi-center study. medRxiv. 2024 Jun 29. link
Ouyang D, Theurer J, Stein NR, Hughes JW, Elias P, He B, Yuan N, Duffy G, Sandhu RK, Ebinger J, Botting P. Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study. The Lancet Digital Health. 2024 Jan 1;6(1):e70-8. link
Cid YD, Macpherson M, Gervais-Andre L, Zhu Y, Franco G, Santeramo R, Lim C, Selby I, Muthuswamy K, Amlani A, Hopewell H. Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study. The Lancet Digital Health. 2024 Jan 1;6(1):e44-57. link
Jiang X, Hoffmeister M, Brenner H, Muti HS, Yuan T, Foersch S, West NP, Brobeil A, Jonnagaddala J, Hawkins N, Ward RL. End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study. The Lancet Digital Health. 2024 Jan 1;6(1):e33-43. link
Greenwood SA, Young HM, Briggs J, Castle EM, Walklin C, Haggis L, Balkin C, Asgari E, Bhandari S, Burton JO, Billany RE. Evaluating the effect of a digital health intervention to enhance physical activity in people with chronic kidney disease (Kidney BEAM): a multicentre, randomised controlled trial in the UK. The Lancet Digital Health. 2024 Jan 1;6(1):e23-32. link
Giddings R, Joseph A, Callender T, Janes SM, Van der Schaar M, Sheringham J, Navani N. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. The Lancet Digital Health. 2024 Feb 1;6(2):e131-44. link
Häggström I, Leithner D, Alvén J, Campanella G, Abusamra M, Zhang H, Chhabra S, Beer L, Haug A, Salles G, Raderer M. Deep learning for [18F] fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis. The Lancet Digital Health. 2024 Feb 1;6(2):e114-25. link
Edgar R, Scholte NT, Ebrahimkheil K, Brouwer MA, Beukema RJ, Mafi-Rad M, Vernooy K, Yap SC, Ronner E, van Mieghem N, Boersma E. Automated cardiac arrest detection using a photoplethysmography wristband: algorithm development and validation in patients with induced circulatory arrest in the DETECT-1 study. The Lancet Digital Health. 2024 Mar 1;6(3):e201-10. link
Villamor MA, Alonso-Sanz M, López-Izquierdo R, Benito JF, del Pozo Vegas C, Torres SL, Soriano JB, Martín-Conty JL, Sanz-García A, Martín-Rodríguez F. Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study. The Lancet Digital Health. 2024 Mar 1;6(3):e166-75. link
Kraljevic Z, Bean D, Shek A, Bendayan R, Hemingway H, Yeung JA, Deng A, Balston A, Ross J, Idowu E, Teo JT. Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study. The Lancet Digital Health. 2024 Apr 1;6(4):e281-90. link
Hu B, Shi Z, Lu L, Miao Z, Wang H, Zhou Z, Zhang F, Wang R, Luo X, Xu F, Li S. A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study. The Lancet Digital Health. 2024 Apr 1;6(4):e261-71. link
Spielvogel CP, Haberl D, Mascherbauer K, Ning J, Kluge K, Traub-Weidinger T, Davies RH, Pierce I, Patel K, Nakuz T, Göllner A. Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study. The Lancet Digital Health. 2024 Apr 1;6(4):e251-60. link
Wei Q, Mease PJ, Chiorean M, Iles-Shih L, Matos WF, Baumgartner A, Molani S, Hwang YM, Belhu B, Ralevski A, Hadlock J. Machine learning to understand risks for severe COVID-19 outcomes: a retrospective cohort study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US health-care system. The Lancet Digital Health. 2024 May 1;6(5):e309-22. link
Lehmann DH, Gomes B, Vetter N, Braun O, Amr A, Hilbel T, Müller J, Köthe U, Reich C, Kayvanpour E, Sedaghat-Hamedani F. Prediction of diagnosis and diastolic filling pressure by AI-enhanced cardiac MRI: a modelling study of hospital data. The Lancet Digital Health. 2024 Jun 1;6(6):e407-17. link
Jung AW, Holm PC, Gaurav K, Hjaltelin JX, Placido D, Mortensen LH, Birney E, Gerstung M. Multi-cancer risk stratification based on national health data: a retrospective modelling and validation study. The Lancet Digital Health. 2024 Jun 1;6(6):e396-406. link
Daniel R, Jones H, Gregory JW, Shetty A, Francis N, Paranjothy S, Townson J. Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm. The Lancet Digital Health. 2024 Jun 1;6(6):e386-95. link
Lopez-Ayala P, Boeddinghaus J, Nestelberger T, Koechlin L, Zimmermann T, Bima P, Glaeser J, Spagnuolo CC, Champetier A, Miro O, Martin-Sanchez FJ. External validation of the myocardial-ischaemic-injury-index machine learning algorithm for the early diagnosis of myocardial infarction: a multicentre cohort study. The Lancet Digital Health. 2024 Jul 1;6(7):e480-8. link
Sau A, Pastika L, Sieliwonczyk E, Patlatzoglou K, Ribeiro AH, McGurk KA, Zeidaabadi B, Zhang H, Macierzanka K, Mandic D, Sabino E. Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study. The Lancet Digital Health. 2024 Nov 1;6(11):e791-802. link
Fisches ZV, Ball M, Mukama T, Štih V, Payne NR, Hickman SE, Gilbert FJ, Bunk S, Leibig C. Strategies for integrating artificial intelligence into mammography screening programmes: a retrospective simulation analysis. The Lancet Digital Health. 2024 Nov 1;6(11):e803-14. link
Ma J, Zhang Y, Gu S, Ge C, Mae S, Young A, Zhu C, Yang X, Meng K, Huang Z, Zhang F. Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge. The Lancet Digital Health. 2024 Nov 1;6(11):e815-26. link
Alderman JE, Charalambides M, Sachdeva G, Laws E, Palmer J, Lee E, Menon V, Malik Q, Vadera S, Calvert M, Ghassemi M. Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review. The Lancet Digital Health. 2024 Nov 1;6(11):e827-47. link
Toprak B, Solleder H, Di Carluccio E, Greenslade JH, Parsonage WA, Schulz K, Cullen L, Apple FS, Ziegler A, Blankenberg S, Stephensen L. Diagnostic accuracy of a machine learning algorithm using point-of-care high-sensitivity cardiac troponin I for rapid rule-out of myocardial infarction: A retrospective study. The Lancet Digital Health. 2024 Oct 1;6(10):e729-38. link
Sengupta PP, Dey D, Davies RH, Duchateau N, Yanamala N. Challenges for augmenting intelligence in cardiac imaging. The Lancet Digital Health. 2024 Oct 1;6(10):e739-48. link
Mihan A, Pandey A, Van Spall HG. Mitigating the risk of artificial intelligence bias in cardiovascular care. The Lancet Digital Health. 2024 Oct 1;6(10):e749-54. link
Myhre PL, Tromp J, Ouwerkerk W, Ting DS, Docherty KF, Gibson CM, Lam CS. Digital tools in heart failure: addressing unmet needs. The Lancet Digital Health. 2024 Oct 1;6(10):e755-66. link
Quer G, Topol EJ. The potential for large language models to transform cardiovascular medicine. The Lancet Digital Health. 2024 Oct 1;6(10):e767-71. link
Qin ZZ, Van der Walt M, Moyo S, Ismail F, Maribe P, Denkinger CM, Zaidi S, Barrett R, Mvusi L, Mkhondo N, Zuma K. Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software. The Lancet Digital Health. 2024 Sep 1;6(9):e605-13. link
Feng X, Goodley P, Alcala K, Guida F, Kaaks R, Vermeulen R, Downward GS, Bonet C, Colorado-Yohar SM, Albanes D, Weinstein SJ. Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis. The Lancet Digital Health. 2024 Sep 1;6(9):e614-24. link
Ueda D, Matsumoto T, Yamamoto A, Walston SL, Mitsuyama Y, Takita H, Asai K, Watanabe T, Abo K, Kimura T, Fukumoto S. A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan. The Lancet Digital Health. 2024 Aug 1;6(8):e580-8. link
Levine DM, Tuwani R, Kompa B, Varma A, Finlayson SG, Mehrotra A, Beam A. The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study. The Lancet Digital Health. 2024 Aug 1;6(8):e555-61. link
Smith LA, Oakden-Rayner L, Bird A, Zeng M, To MS, Mukherjee S, Palmer LJ. Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. The Lancet Digital Health. 2023 Dec 1;5(12):e872-81. link
Beaulieu-Jones BK, Villamar MF, Scordis P, Bartmann AP, Ali W, Wissel BD, Alsentzer E, de Jong J, Patra A, Kohane I. Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study. The Lancet Digital Health. 2023 Dec 1;5(12):e882-94. link
Wang Z, Bian H, Li J, Xu J, Fan H, Wu X, Cao Y, Guo B, Xu X, Wang H, Zhang L. Detection and subtyping of hepatic echinococcosis from plain CT images with deep learning: a retrospective, multicentre study. The Lancet Digital Health. 2023 Nov 1;5(11):e754-62. link
Reinier K, Dizon B, Chugh H, Bhanji Z, Seifer M, Sargsyan A, Uy-Evanado A, Norby FL, Nakamura K, Hadduck K, Shepherd D. Warning symptoms associated with imminent sudden cardiac arrest: a population-based case-control study with external validation. The Lancet Digital Health. 2023 Nov 1;5(11):e763-73. link
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Madani A, Ong JR, Tibrewal A, Mofrad MR. Deep echocardiography: data-efficient supervised and semi-supervised deep learning towards automated diagnosis of cardiac disease. NPJ digital medicine. 2018 Oct 18;1(1):1-1. link
Pieszko K, Shanbhag AD, Singh A, Hauser MT, Miller RJ, Liang JX, Motwani M, Kwieciński J, Sharir T, Einstein AJ, Fish MB. Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging. npj Digital Medicine. 2023 May 1;6(1):78. link
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Yuan N, Stein NR, Duffy G, Sandhu RK, Chugh SS, Chen PS, Rosenberg C, Albert CM, Cheng S, Siegel RJ, Ouyang D. Deep learning evaluation of echocardiograms to identify occult atrial fibrillation. NPJ digital medicine. 2024 Apr 13;7(1):96. link
Zong N, Chowdhury S, Zhou S, Rajaganapathy S, Yu Y, Wang L, Dai Q, Li P, Liu X, Bielinski SJ, Chen J. Advancing efficacy prediction for electronic health records based emulated trials in repurposing heart failure therapies. npj Digital Medicine. 2025 May 24;8(1):306. link
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Hwang T, Lim B, Kwon OS, Kim MH, Kim D, Park JW, Yu HT, Kim TH, Uhm JS, Joung B, Lee MH. Clinical usefulness of digital twin guided virtual amiodarone test in patients with atrial fibrillation ablation. NPJ Digital Medicine. 2024 Oct 23;7(1):297. link
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Barnett M, Wang D, Beadnall H, Bischof A, Brunacci D, Butzkueven H, Brown JW, Cabezas M, Das T, Dugal T, Guilfoyle D. A real-world clinical validation for AI-based MRI monitoring in multiple sclerosis. NPJ digital medicine. 2023 Oct 19;6(1):196. link
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Kainz B, Heinrich MP, Makropoulos A, Oppenheimer J, Mandegaran R, Sankar S, Deane C, Mischkewitz S, Al-Noor F, Rawdin AC, Ruttloff A. Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning. NPJ Digital Medicine. 2021 Sep 15;4(1):137. link
Eng D, Chute C, Khandwala N, Rajpurkar P, Long J, Shleifer S, Khalaf MH, Sandhu AT, Rodriguez F, Maron DJ, Seyyedi S. Automated coronary calcium scoring using deep learning with multicenter external validation. NPJ digital medicine. 2021 Jun 1;4(1):88. link
Huang SC, Kothari T, Banerjee I, Chute C, Ball RL, Borus N, Huang A, Patel BN, Rajpurkar P, Irvin J, Dunnmon J. PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. NPJ digital medicine. 2020 Apr 24;3(1):61. link
Zwack CC, Haghani M, Hollings M, Zhang L, Gauci S, Gallagher R, Redfern J. The evolution of digital health technologies in cardiovascular disease research. NPJ digital medicine. 2023 Jan 3;6(1):1. link
Javaheri T, Homayounfar M, Amoozgar Z, Reiazi R, Homayounieh F, Abbas E, Laali A, Radmard AR, Gharib MH, Mousavi SA, Ghaemi O. CovidCTNet: an open-source deep learning approach to diagnose covid-19 using small cohort of CT images. NPJ digital medicine. 2021 Feb 18;4(1):29. link
Lee CK, Samad M, Hofer I, Cannesson M, Baldi P. Development and validation of an interpretable neural network for prediction of postoperative in-hospital mortality. NPJ digital medicine. 2021 Jan 8;4(1):8. link
Zhou G, Chen Y, Chien C, Revatta L, Ferdous J, Chen M, Deb S, De Leon Cruz S, Wang A, Lee B, Sabuncu MR. Deep learning analysis of blood flow sounds to detect arteriovenous fistula stenosis. NPJ Digital Medicine. 2023 Sep 1;6(1):163. link
Lee H, Yang HL, Ryu HG, Jung CW, Cho YJ, Yoon SB, Yoon HK, Lee HC. Real-time machine learning model to predict in-hospital cardiac arrest using heart rate variability in ICU. NPJ Digital Medicine. 2023 Nov 23;6(1):215. link
Bienefeld N, Boss JM, Lüthy R, Brodbeck D, Azzati J, Blaser M, Willms J, Keller E. Solving the explainable AI conundrum by bridging clinicians’ needs and developers’ goals. npj digital medicine. 2023 May 22;6(1):94. link
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Wang C, Lyu J, Wang S, Qin C, Guo K, Zhang X, Yu X, Li Y, Wang F, Jin J, Shi Z. CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI. Scientific Data. 2024 Jun 25;11(1):687. link
Mayer C, Pepe A, Hossain S, Karner B, Arnreiter M, Kleesiek J, Schmid J, Janisch M, Hannes D, Fuchsjäger M, Zimpfer D. type B aortic Dissection Cta Collection with true and False Lumen Expert annotations for the Development of aI-based algorithms. Scientific Data. 2024 Jun 6;11(1):596. link
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Zhu J, Bai J, Zhou Z, Liang Y, Chen Z, Chen X, Zhang X. RAS dataset: a 3D cardiac LGE-MRI dataset for segmentation of right atrial cavity. Scientific Data. 2024 Apr 20;11(1):401. link
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González S, Hsieh WT, Chen TP. A benchmark for machine-learning based non-invasive blood pressure estimation using photoplethysmogram. Scientific Data. 2023 Mar 21;10(1):149. link
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Pace DF, Contreras HT, Romanowicz J, Ghelani S, Rahaman I, Zhang Y, Gao P, Jubair MI, Yeh T, Golland P, Geva T. HVSMR-2.0: A 3D cardiovascular MR dataset for whole-heart segmentation in congenital heart disease. Scientific Data. 2024 Jul 2;11(1):721. link
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Li YX, Huang JL, Yao XY, Mu SQ, Zong SX, Shen YF. A ballistocardiogram dataset with reference sensor signals in long-term natural sleep environments. Scientific Data. 2024 Oct 5;11(1):1091. link
Xiong Y, Liu T, Chen T, Hansen J, Hu B, Chen Y, Jayaraman G, Schürer S, Vidovic D, Goldfarb J, Sobie EA. Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity. Scientific data. 2022 Jan 20;9(1):18. link
Snoek L, van der Miesen MM, Beemsterboer T, Van Der Leij A, Eigenhuis A, Steven Scholte H. The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses. Scientific data. 2021 Mar 19;8(1):85. link
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Sanches I, Gomes VV, Caetano C, Cabrera LS, Cene VH, Beltrame T, Lee W, Baek S, Penatti OA. MIMIC-BP: A curated dataset for blood pressure estimation. Scientific Data. 2024 Nov 15;11(1):1233. link
Peng X, Li D, Quan J, Wu C, Li H, Liu E, Hu L, Huang S, Kong L, Chen X, Yang H. A multimodal physiological and psychological dataset for human with mental stress induced myocardial ischemia. Scientific Data. 2024 Jun 27;11(1):704. link
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Zheng J, Zhang J, Danioko S, Yao H, Guo H, Rakovski C. A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Scientific data. 2020 Feb 12;7(1):48. link
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Gilon C, Grégoire JM, Mathieu M, Carlier S, Bersini H. IRIDIA-AF, a large paroxysmal atrial fibrillation long-term electrocardiogram monitoring database. Scientific data. 2023 Oct 18;10(1):714. link
Piñeiro-Lamas B, López-Cheda A, Cao R, Ramos-Alonso L, González-Barbeito G, Barbeito-Caamaño C, Bouzas-Mosquera A. A cardiotoxicity dataset for breast cancer patients. Scientific Data. 2023 Aug 8;10(1):527. link
Masoudi M, Pourreza HR, Saadatmand-Tarzjan M, Eftekhari N, Zargar FS, Rad MP. A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism. Scientific data. 2018 Sep 4;5(1):1-9. link
Wagner P, Strodthoff N, Bousseljot RD, Kreiseler D, Lunze FI, Samek W, Schaeffter T. PTB-XL, a large publicly available electrocardiography dataset. Scientific data. 2020 May 25;7(1):1-5. link
Gillette K, Gsell MA, Nagel C, Bender J, Winkler B, Williams SE, Bär M, Schäffter T, Dössel O, Plank G, Loewe A. MedalCare-XL: 16,900 healthy and pathological synthetic 12 lead ECGs from electrophysiological simulations. Scientific Data. 2023 Aug 8;10(1):531. link
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Computed tomography
Huang Z, Chen X, Wang W, Du X, Cao B, Li M, Yang Y, Wang X, Huang J, Zhu J, Zhao X. Prognostic value of non-obstructive coronary artery disease based on coronary computed tomography angiography in a long-term follow-up and multicenter study. Scientific Reports. 2025 May 31;15(1):1-8. link
Salam B, Nowak S, Theis M, Böhner A, Vollbrecht TM, Voigt MB, Endler C, Dell T, Isaak A, Pieper CC, Kuetting D. Associations between cardiac adipose tissue and abdominal visceral fat and muscle based on computed tomography area and density. Scientific Reports. 2025 Jun 20;15(1):1-9. link
Fu M, Qi H, Zhu S, Gao Y, Li Y, Wu J, Zhu D. Computed tomography based radiomics signature for predicting the expression of vascular endothelial growth factor in pediatric patients with nephroblastoma. Scientific Reports. 2025 May 6;15(1):1-0. link
Kim KH, Lee EC, Yoon YD, Shin DW, Koo HW, Lee BJ. Translation of computed tomography images to T2-Weighted magnetic resonance images of lumbar spine using generative adversarial networks on sagittal images. Scientific Reports. 2025 May 26;15(1):1-1. link
Kaphle A, Jayarathna S, Cho SH. Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications. Scientific Reports. 2025 Jun 4;15(1):1-7. link
Kim SC, Lee TY, Kang W, Bae H, Yoon JH, Park S, Moon KH, Cheon SH, Kwon T. Diagnosis and clinical significance of prostate calcification using computed tomography. Scientific Reports. 2025 Feb 8;15(1):4689. link
Krabbe J, Reimers DJ, Otte N, Doukas P, Dirrichs T, Radtke T, Dressel H, Kraus T. Carbon monoxide and nitric oxide diffusion capacity of formerly exposed asbestos workers with high-resolution computed tomography in a cross-sectional study. Scientific Reports. 2025 May 2;15(1):15380. link
Cortes-Puentes GA, Matatko M, Bartholmai BJ, Edell ES, Lim KG. Evaluating physician concordance in interpretation of tracheobronchomalacia diagnosis and phenotyping using dynamic expiratory chest computed tomography. Scientific Reports. 2025 Jan 25;15(1):3278. link
Wang Y, Wang F, Qin Z, Fu Y, Wang J, Li S, Zhang D. A non-invasive diagnostic approach for neuroblastoma utilizing preoperative enhanced computed tomography and deep learning techniques. Scientific Reports. 2025 Apr 26;15(1):14652. link
Matheson BE, Boyd SK. Establishing the effect of computed tomography reconstruction kernels on the measure of bone mineral density in opportunistic osteoporosis screening. Scientific Reports. 2025 Feb 14;15(1):5449. link
Stelbrink C, Jahnke P, Goehler F, Klosterkemper Y, Pumberger M, Schömig F, Tuttle N, Rubarth K, Diekhoff T, Pohlan J. Diagnostic accuracy of dual energy computed tomography for suspected pyogenic spondylodiscitis. Scientific Reports. 2025 Jun 10;15(1):1-9. link
Lee S, Giesen A, Mouselimis D, Weichsel L, Giannopoulos AA, Nunninger M, Renker M, André F, Frey N, Korosoglou G. Composite cardiac computed tomography angiography score for improved risk assessment in chronic coronary syndromes. Scientific Reports. 2025 Jan 24;15(1):3089. link
Ried I, Krinke I, Adolf R, Krönke M, Moosavi SM, Hendrich E, Will A, Bressem K, Hadamitzky M. Incremental diagnostic value of coronary computed tomography angiography derived fractional flow reserve to detect ischemia. Scientific Reports. 2025 Apr 14;15(1):12817. link
Kang SH, Kim K, Shim J, Lee Y. Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods. Scientific Reports. 2025 Apr 17;15(1):13281. link
Liao W, Luo X, Li L, Xu J, He Y, Huang H, Zhang S. Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning. Scientific Reports. 2025 Feb 4;15(1):4250. link
Lee K, Jung W, Jeon J, Chang H, Lee JE, Huh W, Cha WC, Jang HR. Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department. Scientific Reports. 2025 Feb 27;15(1):7088. link
Kong W, Shang L, Long B, Chen X, Mou A, Pu H, Zhang G, Huang H. Impact of physiological and coronary artery disease risk factors on myocardial perfusion in stress computed tomography myocardial perfusion imaging. Scientific Reports. 2025 Feb 10;15(1):4967. link
Hu F, Gu H, Wu F, Lhioui C, Othmen S, Alfahid A, Yousef A, Mercorelli P. Trans pixelate substitution scheme for denoising computed tomography images towards high diagnosis accuracy. Scientific Reports. 2025 Apr 4;15(1):11525. link
Wang X, Wu Q, Xu P, Lu Z. Image reconstruction method based on backprojection filtration algorithm in C-arm computed tomography. Scientific Reports. 2025 Mar 26;15(1):10360. link
Oh S, Kang WY, Park H, Yang Z, Lee J, Kim C, Woo OH, Hong SJ. Evaluation of deep learning-based quantitative computed tomography for opportunistic osteoporosis screening. Scientific Reports. 2024 Jan 5;14(1):363. link
Sun C, Lv J, Liu M, Ma H. Different scanning protocol to assess left atrial appendage thrombus in patients with atrial fibrillation by cardiovascular computed tomography. Scientific Reports. 2024 Dec 6;14(1):1-7. link
Nakao Y, Nishihara T, Sasaki R, Fukushima M, Miuma S, Miyaaki H, Akazawa Y, Nakao K. Investigation of deep learning model for predicting immune checkpoint inhibitor treatment efficacy on contrast-enhanced computed tomography images of hepatocellular carcinoma. Scientific Reports. 2024 Mar 19;14(1):6576. link
De Lorenzo A, dos Santos Fernandes MC, Romeiro F, Arpini AP, Dias GM. DNA damage and repair in patients undergoing myocardial perfusion single-photon emission computed tomography. Scientific Reports. 2024 Jun 7;14(1):13079. link
Kim JY, Lee C, Park YL, Lee JH, Ryu YH, Huh JK. Diagnostic criteria for temporomandibular joint osteoarthritis using standardized uptake value in single-photon emission computed tomography–computed tomography. Scientific Reports. 2024 Dec 30;14(1):31569. link
Huang Z, Tang R, Ding Y, Wang X, Du X, Wang W, Li Z, Xiao J, Wang X. Lack of incremental prognostic value of triglyceride glucose index beyond coronary computed tomography angiography features for major events. Scientific Reports. 2024 Oct 27;14(1):25670. link
Saillard E, Gardegaront M, Levillain A, Bermond F, Mitton D, Pialat JB, Confavreux C, Grenier T, Follet H. Finite element models with automatic computed tomography bone segmentation for failure load computation. Scientific Reports. 2024 Jul 17;14(1):16576. link
Hirata T, Yoshimura N, Yagi T, Yamazaki M, Horii Y, Ishikawa H. Association between pre-treatment computed tomography findings and post-treatment persistent decrease in lung perfusion blood volume. Scientific Reports. 2024 May 24;14(1):11919. link
Wang S, Sun Z, Zeng Y, Xu X, Wang Y, Liu X, Yang Y. Feasibility study of ‘Triple-Low’technique for coronary artery computed tomography angiography (CCTA). Scientific Reports. 2024 Dec 30;14(1):32110. link
Wirtensohn S, Schmid C, Berthe D, John D, Heck L, Taphorn K, Flenner S, Herzen J. Self-supervised denoising of grating-based phase-contrast computed tomography. Scientific Reports. 2024 Dec 31;14(1):32169. link
Han S, Lee J, Lee JK. Neural network-based automated proptosis measurement using computed tomography images for patients with thyroid-associated orbitopathy. Scientific Reports. 2024 Nov 8;14(1):27268. link
Chen X, Liang T, Liu C, Ren J, Su S, Long X, Yin X, Chen Y, Jiang S, Wang K. Sex differences in shoulder acromiohumeral contact surface arc length on three-dimensional computed tomography imaging. Scientific Reports. 2024 Nov 21;14(1):28813. link
Mostafa K, Seoudy H, Aludin S, Schunk D, Peckolt H, Wolf C, Saad M, Both M, Jansen O, Frank D, Langguth P. Computed tomography for the detection of myocardial hypoperfusion in acute myocardial infarction and the associated CT-to-catheter time. Scientific Reports. 2024 Oct 18;14(1):24456. link
Lye R, Min H, Dowling J, Obertová Z, Estai M, Bachtiar NA, Franklin D. Deep learning versus human assessors: forensic sex estimation from three-dimensional computed tomography scans. Scientific Reports. 2024 Dec 3;14(1):1-2. link
Paakkari P, Inkinen SI, Mohammadi A, Nieminen MT, Joenathan A, Grinstaff MW, Töyräs J, Mäkelä JT, Honkanen JT. Photon-counting in dual-contrast-enhanced computed tomography: a proof-of-concept quantitative biomechanical assessment of articular cartilage. Scientific Reports. 2024 Dec 2;14(1):1-4. link
Jang DH, Lee J, Jeon YJ, Yoon YE, Ahn H, Kang BK, Choi WS, Oh J, Lee DK. Kidney, ureter, and urinary bladder segmentation based on non-contrast enhanced computed tomography images using modified U-Net. Scientific Reports. 2024 Jul 3;14(1):15325. link
Zhang F, Song HX, He ZP, Zheng LH, Han YR, Wang BY, Liu P. Analysis of computed tomography venography for the diagnosis and endovascular treatment of iliac venous compression syndrome with venous leg ulcers: a retrospective study. Scientific Reports. 2024 Sep 27;14(1):22314. link
Fan YJ, Ng Y, Tzeng IS, Hsu YY, Cheng YL, Zhou JH. Enhancing pectus excavatum diagnosis with an automated batch evaluation tool for chest computed tomography images. Scientific Reports. 2024 Oct 8;14(1):23468. link
Nagawa K, Hara Y, Shimizu H, Matsuura K, Inoue K, Kozawa E, Sakaguchi K, Niitsu M. Sectional measurements of shoulder muscle volume and computed tomography density in anterior shoulder instability. Scientific Reports. 2024 Nov 10;14(1):27436. link
Kim JS, Kwon D, Kim K, Lee SH, Lee SB, Kim K, Kim D, Lee MW, Park N, Choi JH, Jang ES. Machine learning-based prediction of pulmonary embolism to reduce unnecessary computed tomography scans in gastrointestinal cancer patients: a retrospective multicenter study. Scientific Reports. 2024 Oct 25;14(1):25359. link
Zegadło A, Różyk A, Żabicka M, Więsik–Szewczyk E, Maliborski A. Dual-energy computed tomography as a lower radiation dose alternative to perfusion computed tomography in tumor viability assessment. Scientific Reports. 2023 Jan 4;13(1):120. link
Ozawa A, Iwasaki M, Yokoyama K, Tsuchiya J, Kawano R, Nishihara H, Tateishi U. Correlation between choline kinase alpha expression and 11C-choline accumulation in breast cancer using positron emission tomography/computed tomography: a retrospective study. Scientific reports. 2023 Oct 17;13(1):17620. link
Lee K, Kim YI, Oh JS, Seo SY, Yun JK, Lee GD, Choi S, Kim HR, Kim YH, Kim DK, Park SI. [18F] fluorodeoxyglucose positron emission tomography/computed tomography characteristics of primary mediastinal germ cell tumors. Scientific Reports. 2023 Oct 17;13(1):17619. link
Zhang C, Zhang W, Shi K, Chen J. Application of double low-dose mode in left atrial-pulmonary venous computed tomography angiography. Scientific Reports. 2023 Dec 7;13(1):21563. link
Lee NH, Kim SH, Seo SH, Kim BJ, Lee CS, Kim GH, Park SJ, Kim SH, Ryu DY, Kim HH, Lee SB. Prediction of respiratory complications by quantifying lung contusion volume using chest computed tomography in patients with chest trauma. Scientific Reports. 2023 Apr 19;13(1):6387. link
Simon J, Mikhael P, Tahir I, Graur A, Ringer S, Fata A, Jeffrey YC, Shepard JA, Jacobson F, Barzilay R, Sequist LV. Role of sex in lung cancer risk prediction based on single low-dose chest computed tomography. Scientific reports. 2023 Oct 30;13(1):18611. link
Siika A, Bogdanovic M, Liljeqvist ML, Gasser TC, Hultgren R, Roy J. Three-dimensional growth and biomechanical risk progression of abdominal aortic aneurysms under serial computed tomography assessment. Scientific Reports. 2023 Jun 7;13(1):9283. link
Kim SY, Suh YJ, Lee HJ, Kim YJ. Prognostic value of coronary artery calcium scores from 1.5 mm slice reconstructions of electrocardiogram-gated computed tomography scans in asymptomatic individuals. Scientific reports. 2022 May 3;12(1):7198. link
Lim WH, Park CM. Validation for measurements of skeletal muscle areas using low-dose chest computed tomography. Scientific Reports. 2022 Jan 10;12(1):463. link
Komiya K, Yamasue M, Goto A, Nakamura Y, Hiramatsu K, Kadota JI, Kato S. High-resolution computed tomography features associated with differentiation of tuberculosis among elderly patients with community-acquired pneumonia: a multi-institutional propensity-score matched study. Scientific Reports. 2022 May 6;12(1):7466. link
Lim SH, Kim YJ, Park YH, Kim D, Kim KG, Lee DH. Automated pancreas segmentation and volumetry using deep neural network on computed tomography. Scientific Reports. 2022 Mar 8;12(1):4075. link
Chang MY, Liou YD, Huang JH, Su CH, Huang SC, Lin MT, Chen SJ. Dynamic cardiac computed tomography characteristics of double-chambered right ventricle. Scientific Reports. 2022 Nov 29;12(1):20607. link
Hanai K, Tabuchi H, Nagasato D, Tanabe M, Masumoto H, Miya S, Nishio N, Nakamura H, Hashimoto M. Automated detection of enlarged extraocular muscle in Graves’ ophthalmopathy with computed tomography and deep neural network. Scientific reports. 2022 Sep 26;12(1):16036. link
Ohata K, Chen-Yoshikawa TF, Hamaji M, Kubo T, Nakamura T, Date H. Radiologic evaluation of compensatory lung growth using computed tomography by comparison with histological data from a large animal model. Scientific Reports. 2022 Feb 15;12(1):2520. link
Seppelt D, Kromrey ML, Ittermann T, Kolb C, Haubold A, Kampfrath N, Fedders D, Heiss P, Hoberück S, Hoffmann RT, Kühn JP. Reliability and accuracy of straightforward measurements for liver volume determination in ultrasound and computed tomography compared to real volumetry. Scientific Reports. 2022 Jul 21;12(1):12465. link
Abbasi B, Seyed Hosseini M, Moodi Ghalibaf A, Akhavan R, Emadzadeh M, Bolvardi E. Evaluating anemia on non-contrast thoracic computed tomography. Scientific Reports. 2022 Dec 10;12(1):21380. link
Riffel J, Lübke J, Naumann N, Kreil S, Metzgeroth G, Fabarius A, Sotlar K, Horny HP, Jawhar M, Overhoff D, Schoenberg S. Functional imaging with dual-energy computed tomography for supplementary non-invasive assessment of mast cell burden in systemic mastocytosis. Scientific reports. 2022 Aug 20;12(1):14228. link
Higuchi S, Nishii T, Hirota A, Harumoto S, Horinouchi H, Tateishi E, Ohta Y, Kiso K, Kurosaki K, Fukuda T. Patient positioning during pediatric cardiothoracic computed tomography using a high-resilience pad system and pre-scan measurement of chest thickness. Scientific Reports. 2022 Oct 5;12(1):16618. link
Fukumoto W, Kitera N, Mitani H, Sueoka T, Kondo S, Kawashita I, Nakamura Y, Nagao M, Awai K. Global illumination rendering versus volume rendering for the forensic evaluation of stab wounds using computed tomography. Scientific Reports. 2022 Feb 14;12(1):2452. link
Gaume M, Chevret S, Campagna R, Larousserie F, Biau D. The appropriate and sequential value of standard radiograph, computed tomography and magnetic resonance imaging to characterize a bone tumor. Scientific Reports. 2022 Apr 13;12(1):6196. link
Han S, Jeon YJ, Lee TY, Park GM, Park S, Kim SC. Testosterone is associated with abdominal body composition derived from computed tomography: a large cross sectional study. Scientific Reports. 2022 Dec 29;12(1):22528. link
Kumasaka S, Kumasaka Y, Jingu A, Tsushima Y. Diagnostic value of “hyperdense consolidation sign” as a characteristic new computed tomography sign of diffuse alveolar hemorrhage. Scientific Reports. 2022 Dec 7;12(1):21143. link
Al Rifai M, Ahmed AI, Han Y, Saad JM, Alnabelsi T, Nabi F, Chang SM, Cocker M, Schwemmer C, Ramirez-Giraldo JC, Zoghbi WA. Sex differences in machine learning computed tomography-derived fractional flow reserve. Scientific Reports. 2022 Aug 16;12(1):13861. link
Lee M, Lee E, Lee JW. Value of computed tomography Hounsfield units in predicting pedicle screw loosening in the thoracic spine. Scientific Reports. 2022 Oct 31;12(1):18279. link
Javan-Noughabi J, Rezapour A, Hajahmadi M, Alipour V. Economic evaluation of single-photon emission-computed tomography versus stress echocardiography in stable chest pain patients. Scientific Reports. 2022 Sep 8;12(1):15223. link
Niiya A, Murakami K, Kobayashi R, Sekimoto A, Saeki M, Toyofuku K, Kato M, Shinjo H, Ito Y, Takei M, Murata C. Development of an artificial intelligence-assisted computed tomography diagnosis technology for rib fracture and evaluation of its clinical usefulness. Scientific Reports. 2022 May 19;12(1):8363. link
Sugiura J, Watanabe M, Nobuta S, Okamura A, Kyodo A, Nakamura T, Nogi K, Ishihara S, Hashimoto Y, Ueda T, Seno A. Prediction of optical coherence tomography-detected calcified nodules using coronary computed tomography angiography. Scientific Reports. 2022 Dec 24;12(1):22296. link
Kravchenko D, Hart C, Garbe S, Luetkens JA, Isaak A, Mesropyan N, Vergnat M, Leyens J, Attenberger U, Kuetting D. Image quality and radiation dose of dual source high pitch computed tomography in pediatric congenital heart disease. Scientific reports. 2022 Jun 15;12(1):9934. link
Ichikawa S, Hamada M, Sugimori H. A deep-learning method using computed tomography scout images for estimating patient body weight. Scientific reports. 2021 Aug 2;11(1):15627. link
Reimer RP, Klein K, Rinneburger M, Zopfs D, Lennartz S, Salem J, Heidenreich A, Maintz D, Haneder S, Große Hokamp N. Manual kidney stone size measurements in computed tomography are most accurate using multiplanar image reformatations and bone window settings. Scientific Reports. 2021 Aug 12;11(1):16437. link
Soffer S, Klang E, Shimon O, Barash Y, Cahan N, Greenspana H, Konen E. Deep learning for pulmonary embolism detection on computed tomography pulmonary angiogram: a systematic review and meta-analysis. Scientific reports. 2021 Aug 4;11(1):15814. link
Kreutzinger V, Diekhoff T, Liefeldt L, Poddubnyy D, Hermann KG, Ziegeler K. Asymptomatic secondary hyperparathyroidism can mimic sacroiliitis on computed tomography. Scientific Reports. 2021 Feb 22;11(1):4323. link
Hong D, Kim H, Kim T, Kim YH, Kim N. Development of patient specific, realistic, and reusable video assisted thoracoscopic surgery simulator using 3D printing and pediatric computed tomography images. Scientific Reports. 2021 Mar 18;11(1):6191. link
Wang P, Pei X, Yin XP, Ren JL, Wang Y, Ma LY, Du XG, Gao BL. Radiomics models based on enhanced computed tomography to distinguish clear cell from non-clear cell renal cell carcinomas. Scientific Reports. 2021 Jul 2;11(1):13729. link
Poilliot A, Doyle T, Kurosawa D, Toranelli M, Zhang M, Zwirner J, Müller-Gerbl M, Hammer N. Computed tomography osteoabsorptiometry-based investigation on subchondral bone plate alterations in sacroiliac joint dysfunction. Scientific reports. 2021 Apr 21;11(1):8652. link
Peper J, Schaap J, Kelder JC, Rensing BJ, Grobbee DE, Leiner T, Swaans MJ. Added value of computed tomography fractional flow reserve in the diagnosis of coronary artery disease. Scientific reports. 2021 Mar 24;11(1):6748. link
Pan LS, Li CW, Su SF, Tay SY, Tran QV, Chan WP. Coronary artery segmentation under class imbalance using a U-Net based architecture on computed tomography angiography images. Scientific reports. 2021 Jul 14;11(1):14493. link
Stoll-Dannenhauer T, Schwab G, Zahn K, Schaible T, Wessel L, Weiss C, Schoenberg SO, Henzler T, Weis M. Computed tomography based measurements to evaluate lung density and lung growth after congenital diaphragmatic hernia. Scientific reports. 2021 Mar 3;11(1):5035. link
Li S, Liu J, Xiong Y, Pang P, Lei P, Zou H, Zhang M, Fan B, Luo P. A radiomics approach for automated diagnosis of ovarian neoplasm malignancy in computed tomography. Scientific reports. 2021 Apr 22;11(1):8730. link
Chu H, Pang P, He J, Zhang D, Zhang M, Qiu Y, Li X, Lei P, Fan B, Xu R. Value of radiomics model based on enhanced computed tomography in risk grade prediction of gastrointestinal stromal tumors. Scientific Reports. 2021 Jun 8;11(1):12009. link
Guo H, Liu W, Wang J, Xing Y. Extrahepatic alveolar echinococcus on multi-slice computed tomography and magnetic resonance imaging. Scientific Reports. 2021 Apr 30;11(1):9409. link
Yajima T, Arao M, Yajima K, Takahashi H. Usefulness of computed tomography-measured psoas muscle thickness per height for predicting mortality in patients undergoing hemodialysis. Scientific reports. 2021 Sep 24;11(1):19070. link
Moon SW, Kim SY, Choi JS, Leem AY, Lee SH, Park MS, Kim YS, Chung KS. Thoracic skeletal muscle quantification using computed tomography and prognosis of elderly ICU patients. Scientific Reports. 2021 Dec 6;11(1):23461. link
Handke NA, Koch DC, Muschler E, Thomas D, Luetkens JA, Attenberger UI, Kuetting D, Pieper CC, Wilhelm K. Bleeding management in computed tomography-guided liver biopsies by biopsy tract plugging with gelatin sponge slurry. Scientific Reports. 2021 Dec 30;11(1):24506. link
Maschke SK, Werncke T, Dewald CL, Becker LS, Meine TC, Olsson KM, Hoeper MM, Wacker FK, Meyer BC, Hinrichs JB. Depiction of mosaic perfusion in chronic thromboembolic pulmonary hypertension (CTEPH) on C-arm computed tomography compared to computed tomography pulmonary angiogram (CTPA). Scientific Reports. 2021 Oct 8;11(1):20042. link
Hyeon CW, Yi HK, Kim EK, Park SJ, Lee SC, Park SW, Oh JK, Choi JY, Chang SA. The role of 18F-fluorodeoxyglucose-positron emission tomography/computed tomography in the differential diagnosis of pericardial disease. Scientific reports. 2020 Dec 9;10(1):21524. link
Huh J, Park SJ, Lee JK. Measurement of proptosis using computed tomography based three-dimensional reconstruction software in patients with Graves’ orbitopathy. Scientific Reports. 2020 Sep 3;10(1):14554. link
Pham TD. A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks. Scientific reports. 2020 Oct 9;10(1):16942. link
Zheng X, Al-Hayek Y, Cummins C, Li X, Nardi L, Albari K, Evans J, Roworth E, Seaton T. Body size and tube voltage dependent corrections for Hounsfield Unit in medical X-ray computed tomography: theory and experiments. Scientific Reports. 2020 Sep 24;10(1):15696. link
Jin L, Gao Y, Sun Y, Li C, Gao P, Zhao W, Li M. Contrast medium administration with a body surface area protocol in step-and-shoot coronary computed tomography angiography with dual-source scanners. Scientific Reports. 2020 Oct 7;10(1):16690. link
Li IG, Yang YH, Li YT, Tsai YH. Paediatric computed tomography and subsequent risk of leukaemia, intracranial malignancy and lymphoma: a nationwide population-based cohort study. Scientific Reports. 2020 May 8;10(1):7759. link
Song WH, Baik J, Choi EK, Lee HY, Kim HH, Park SM, Jeong CW. Quantitative analysis of renal arterial variations affecting the eligibility of catheter-based renal denervation using multi-detector computed tomography angiography. Scientific Reports. 2020 Nov 12;10(1):19720. link
Hirose TA, Arimura H, Ninomiya K, Yoshitake T, Fukunaga JI, Shioyama Y. Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy. Scientific reports. 2020 Nov 24;10(1):20424. link
Wu H, Chen X, Zhou H, Qin B, Cao J, Pan Z, Wang Z. An optimized test bolus for computed tomography pulmonary angiography and its application at 80 kV with 10 ml contrast agent. Scientific reports. 2020 Jun 23;10(1):10208. link
Huang Z, Xiao J, Xie Y, Hu Y, Zhang S, Li X, Wang Z, Li Z, Wang X. The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography. Scientific reports. 2020 Jul 13;10(1):11532. link
Lee SJ, Park HJ. Single photon emission computed tomography (SPECT) or positron emission tomography (PET) imaging for radiotherapy planning in patients with lung cancer: a meta-analysis. Scientific Reports. 2020 Sep 10;10(1):14864. link
Ji Y, Shao C, Cui Y, Shao G, Zheng J. 18F-FDG positron-emission tomography/computed tomography findings of radiographic lesions suggesting old healed pulmonary tuberculosis and high-risk signs of predicting recurrence: a retrospective study. Scientific Reports. 2019 Aug 29;9(1):12582. link
Kulpe S, Dierolf M, Günther B, Busse M, Achterhold K, Gleich B, Herzen J, Rummeny E, Pfeiffer F, Pfeiffer D. K-edge subtraction computed tomography with a compact synchrotron X-ray source. Scientific reports. 2019 Sep 16;9(1):13332. link
Lee J, Kim TH, Lee BK, Yoon YW, Kwon HM, Hong BK, Min PK, Choi EY, Oh CS, Park CH. Diagnostic accuracy of low-radiation coronary computed tomography angiography with low tube voltage and knowledge-based model reconstruction. Scientific reports. 2019 Feb 4;9(1):1308. link
Hiyama A, Katoh H, Sakai D, Sato M, Tanaka M, Nukaga T, Watanabe M. Changes in spinal alignment following extreme lateral interbody fusion alone in patients with adult spinal deformity using computed tomography. Scientific Reports. 2019 Aug 19;9(1):12039. link
Garcia TS, Engelholm JL, Vouche M, Hirakata VN, Leitão CB. Intra-and interobserver reproducibility of pancreatic perfusion by computed tomography. Scientific reports. 2019 Apr 15;9(1):6043. link
Zhao Q, Wang J, Yang ZG, Shi K, Diao KY, Huang S, Shen MT, Guo YK. Assessment of intracardiac and extracardiac anomalies associated with coarctation of aorta and interrupted aortic arch using dual-source computed tomography. Scientific reports. 2019 Aug 12;9(1):11656. link
Anan K, Ichikado K, Ishihara T, Shintani A, Kawamura K, Suga M, Sakagami T. A scoring system with high-resolution computed tomography to predict drug-associated acute respiratory distress syndrome: development and internal validation. Scientific Reports. 2019 Jun 13;9(1):8601. link
Strong C, Ferreira A, Teles RC, Mendes G, Abecasis J, Cardoso G, Guerreiro S, Freitas P, Santos AC, Saraiva C, Brito J. Diagnostic accuracy of computed tomography angiography for the exclusion of coronary artery disease in candidates for transcatheter aortic valve implantation. Scientific reports. 2019 Dec 27;9(1):19942. link
Mackin D, Ger R, Dodge C, Fave X, Chi PC, Zhang L, Yang J, Bache S, Dodge C, Jones AK, Court L. Effect of tube current on computed tomography radiomic features. Scientific reports. 2018 Feb 5;8(1):2354. link
Yuan M, Liu JY, Zhang T, Zhang YD, Li H, Yu TF. Prognostic Impact of the Findings on Thin-Section Computed Tomography in stage I lung adenocarcinoma with visceral pleural invasion. Scientific Reports. 2018 Mar 16;8(1):4743. link
Oshina M, Oshima Y, Tanaka S, Tan LA, Li XJ, Tuchman A, Riew KD. Utility of oblique sagittal reformatted and three-dimensional surface reconstruction computed tomography in foraminal stenosis decompression. Scientific reports. 2018 Oct 30;8(1):16011. link
Mann C, Ziegeler K, Mews J, Plaschke M, Issever AS. Bone mineral density assessment using iterative reconstruction compared with quantitative computed tomography as the standard of reference. Scientific Reports. 2018 Oct 10;8(1):15095. link
Gallus S, Lugo A, Suatoni P, Taverna F, Bertocchi E, Boffi R, Marchiano A, Morelli D, Pastorino U. Effect of tobacco smoking cessation on C-reactive protein levels in a cohort of low-dose computed tomography screening participants. Scientific reports. 2018 Aug 27;8(1):12908. link
Dieker W, Behnes M, Fastner C, Sartorius B, Wenke A, Sing-Gill I, El-Battrawy I, Kuschyk J, Papavassiliu T, Hoffmann U, Mashayekhi K. Impact of left atrial appendage morphology on thrombus formation after successful left atrial appendage occlusion: assessment with cardiac-computed-tomography. Scientific Reports. 2018 Jan 26;8(1):1670. link
Guo F, Zhu G, Shen J, Ma Y. Health risk stratification based on computed tomography pulmonary artery obstruction index for acute pulmonary embolism. Scientific Reports. 2018 Dec 17;8(1):17897. link
Gao Y, Yang ZG, Shi K, Diao KY, Xu HY, Guo YK. Computed tomography for evaluating right ventricle and pulmonary artery in pediatric tetralogy of Fallot: correlation with post-operative pulmonary regurgitation. Scientific Reports. 2018 May 14;8(1):7515. link
Sun K, Han R, Han Y, Shi X, Hu J, Lu B. Accuracy of combined computed tomography colonography and dual energy iiodine map imaging for detecting colorectal masses using high-pitch dual-source CT. Scientific Reports. 2018 Feb 28;8(1):3790. link
Xu R, Shi K, Yang ZG, Diao KY, Zhao Q, Xu HY, Guo YK. Quantified evaluation of tracheal compression in pediatric complex congenital vascular ring by computed tomography. Scientific Reports. 2018 Jul 25;8(1):11183. link
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Hong YJ, Hur J, Han K, Im DJ, Suh YJ, Lee HJ, Kim YJ, Choi BW. Quantitative analysis of a whole cardiac mass using dual-energy computed tomography: comparison with conventional computed tomography and magnetic resonance imaging. Scientific reports. 2018 Oct 18;8(1):15334. link
Yang MX, Yang ZG, Zhang Y, Shi K, Xu HY, Diao KY, Guo YK. Dual-source computed tomography for evaluating pulmonary artery and aorta in pediatric patients with single ventricle. Scientific Reports. 2017 Oct 17;7(1):13398. link
Kiryu S, Akai H, Nojima M, Hasegawa K, Shinkawa H, Kokudo N, Yasaka K, Ohtomo K. Impact of hepatocellular carcinoma heterogeneity on computed tomography as a prognostic indicator. Scientific reports. 2017 Oct 4;7(1):12689. link
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Lee BC, Chang CC, Liu KL, Chang YC, Wu VC, Huang KH. Evaluation of right adrenal vein anatomy by Dyna computed tomography in patients with primary aldosteronism. Scientific reports. 2016 Jun 23;6(1):28305. link
Chang CC, Lee BC, Liu KL, Chang YC, Wu VC, Huang KH. Non-stimulated adrenal venous sampling using Dyna computed tomography in patients with primary aldosteronism. Scientific Reports. 2016 Nov 23;6(1):37143. link
Bernstein AL, Dhanantwari A, Jurcova M, Cheheltani R, Naha PC, Ivanc T, Shefer E, Cormode DP. Improved sensitivity of computed tomography towards iodine and gold nanoparticle contrast agents via iterative reconstruction methods. Scientific reports. 2016 May 17;6(1):26177. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
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Bashivan P, Kar K, DiCarlo JJ. Neural population control via deep image synthesis. Science. 2019 May 3;364(6439):eaav9436. link
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Others
Li Y, Choi D, Chung J, Kushman N, Schrittwieser J, Leblond R, Eccles T, Keeling J, Gimeno F, Dal Lago A, Hubert T. Competition-level code generation with alphacode. Science. 2022 Dec 9;378(6624):1092-7. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Yang J, Grafton F, Ranjbarvaziri S, Budan A, Farshidfar F, Cho M, Xu E, Ho J, Maddah M, Loewke KE, Medina J. Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy. Science translational medicine. 2022 Jul 6;14(652):eabl5654. link
Xu S, Kim J, Walter JR, Ghaffari R, Rogers JA. Translational gaps and opportunities for medical wearables in digital health. Science translational medicine. 2022 Oct 12;14(666):eabn6036. link
Witowski J, Heacock L, Reig B, Kang SK, Lewin A, Pysarenko K, Patel S, Samreen N, Rudnicki W, Łuczyńska E, Popiela T. Improving breast cancer diagnostics with deep learning for MRI. Science translational medicine. 2022 Sep 28;14(664):eabo4802. link
Eriksson M, Destounis S, Czene K, Zeiberg A, Day R, Conant EF, Schilling K, Hall P. A risk model for digital breast tomosynthesis to predict breast cancer and guide clinical care. Science Translational Medicine. 2022 May 11;14(644):eabn3971. link
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Ji S, Feng L, Fu Z, Wu G, Wu Y, Lin Y, Lu D, Song Y, Cui P, Yang Z, Sang C. Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology. Science translational medicine. 2023 Jul 26;15(706):eadg3358. link
Zekavat SM, Jorshery SD, Rauscher FG, Horn K, Sekimitsu S, Koyama S, Nguyen TT, Costanzo MC, Jang D, Burtt NP, Kühnapfel A. Phenome-and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health. Science Translational Medicine. 2024 Jan 24;16(731):eadg4517. link
Soenksen LR, Kassis T, Conover ST, Marti-Fuster B, Birkenfeld JS, Tucker-Schwartz J, Naseem A, Stavert RR, Kim CC, Senna MM, Avilés-Izquierdo J. Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images. Science Translational Medicine. 2021 Feb 17;13(581):eabb3652. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
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Verma R, Alban TJ, Parthasarathy P, Mokhtari M, Toro Castano P, Cohen ML, Lathia JD, Ahluwalia M, Tiwari P. Sexually dimorphic computational histopathological signatures prognostic of overall survival in high-grade gliomas via deep learning. Science advances. 2024 Aug 23;10(34):eadi0302. link
Basu A. Use of race in clinical algorithms. Science Advances. 2023 May 26;9(21):eadd2704. link
Zhang T, Cheng X, Jia S, Li CT, Poo MM, Xu B. A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost. Science Advances. 2023 Aug 25;9(34):eadi2947. link
Zhang T, Cheng X, Jia S, Poo MM, Zeng Y, Xu B. Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks. Science advances. 2021 Oct 20;7(43):eabh0146. link
Tiwari S, Kajdacsy-Balla A, Whiteley J, Cheng G, Jirstrom K, Birgisson H, Hewitt SM, Bhargava R. INFORM: INFrared-based ORganizational Measurements of tumor and its microenvironment to predict patient survival. Science Advances. 2021 Feb 3;7(6):eabb8292. link
Ganzer PD, Loeian MS, Roof SR, Teng B, Lin L, Friedenberg DA, Baumgart IW, Meyers EC, Chun KS, Rich A, Tsao AL. Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine. Science advances. 2022 Jan 5;8(1):eabj5473. link
Spitale G, Biller-Andorno N, Germani F. AI model GPT-3 (dis) informs us better than humans. Science Advances. 2023 Jun 28;9(26):eadh1850. link
Sizemore N, Oliphant K, Zheng R, Martin CR, Claud EC, Chattopadhyay I. A digital twin of the infant microbiome to predict neurodevelopmental deficits. Science Advances. 2024 Apr 10;10(15):eadj0400. link
Shade JK, Prakosa A, Popescu DM, Yu R, Okada DR, Chrispin J, Trayanova NA. Predicting risk of sudden cardiac death in patients with cardiac sarcoidosis using multimodality imaging and personalized heart modeling in a multivariable classifier. Science Advances. 2021 Jul 28;7(31):eabi8020. link
Prince JS, Alvarez GA, Konkle T. Contrastive learning explains the emergence and function of visual category-selective regions. Science Advances. 2024 Sep 25;10(39):eadl1776. link
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Li Q, Ren Z, Cao K, Li MM, Wang K, Zhou Y. CancerVar: An artificial intelligence–empowered platform for clinical interpretation of somatic mutations in cancer. Science advances. 2022 May 6;8(18):eabj1624. link
Liboni LH, Budzinski RC, Busch AN, Löwe S, Keller TA, Welling M, Muller LE. Image segmentation with traveling waves in an exactly solvable recurrent neural network. Proceedings of the National Academy of Sciences. 2025 Jan 7;122(1):e2321319121. link
Weaver DT, King ES, Maltas J, Scott JG. Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance. Proceedings of the National Academy of Sciences. 2024 Apr 16;121(16):e2303165121. link
Yang R, Xiao T, Cheng Y, Li A, Qu J, Liang R, Bao S, Wang X, Wang J, Suo J, Luo Q. Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function. Proceedings of the National Academy of Sciences. 2024 Jul 9;121(28):e2320870121. link
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Steyvers M, Tejeda H, Kerrigan G, Smyth P. Bayesian modeling of human–AI complementarity. Proceedings of the National Academy of Sciences. 2022 Mar 15;119(11):e2111547119. link
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Cramer EY, Ray EL, Lopez VK, Bracher J, Brennen A, Castro Rivadeneira AJ, Gerding A, Gneiting T, House KH, Huang Y, Jayawardena D. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences. 2022 Apr 12;119(15):e2113561119. link
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AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Burley SK, Arap W, Pasqualini R. Predicting proteome-scale protein structure with artificial intelligence. New England Journal of Medicine. 2021 Dec 2;385(23):2191-4. link
Milea D, Najjar RP, Jiang Z, Ting D, Vasseneix C, Xu X, Aghsaei Fard M, Fonseca P, Vanikieti K, Lagrèze WA, La Morgia C. Artificial intelligence to detect papilledema from ocular fundus photographs. New England Journal of Medicine. 2020 Apr 30;382(18):1687-95. link
Taylor RA, Chmura C, Hinson J, Steinhart B, Sangal R, Venkatesh AK, Xu H, Cohen I, Faustino IV, Levin S. Impact of artificial intelligence–based triage decision support on emergency department care. NEJM AI. 2025 Feb 27;2(3):AIoa2400296. link
Adnan T, Islam MS, Lee S, Wasifur Rahman Chowdhury EM, Tithi SD, Noshin K, Islam MR, Sarker I, Rahman MS, Schneider RB, Adams JL. AI-Enabled Parkinson’s Disease Screening Using Smile Videos. NEJM AI. 2025 Jun 26;2(7):AIoa2400950. link
Taylor RA, Chmura C, Hinson J, Steinhart B, Sangal R, Venkatesh AK, Xu H, Cohen I, Faustino IV, Levin S. Impact of artificial intelligence–based triage decision support on emergency department care. NEJM AI. 2025 Feb 27;2(3):AIoa2400296. link
Lampert J, Bhatt DL, Vaid A, Kon K, Feinman J, Jou S, Kauffman J, Nadkarni G, Reddy VY. Calibration of ECG-based deep-learning algorithm scores for patients flagged as high risk for hypertrophic cardiomyopathy. NEJM AI. 2025 Apr 24;2(5):AIoa2400421. link
Lee B, Patel S, Favorito C, Sandri S, Jennings MR, Dai T. Development and commercialization pathways of AI medical devices in the United States: implications for safety and regulatory oversight. NEJM AI. 2025 Jun 26;2(7):AIra2500061. link
Dai W, Adeli E, Luo Z, Dash D, Lakshmikanth S, Durante Z, Tang P, Kaushal A, Milstein A, Fei-Fei L, Schulman K. Developing ICU Clinical Behavioral Atlas Using Ambient Intelligence and Computer Vision. NEJM AI. 2025 Jan 21:AIoa2400590. link
de Castro DC, Bustos A, Bannur S, Hyland SL, Bouzid K, Wetscherek MT, Sánchez-Valverde MD, Jaques-Pérez L, Pérez-Rodríguez L, Takeda K, Salinas-Serrano JM. Padchest-gr: A bilingual chest x-ray dataset for grounded radiology report generation. NEJM AI. 2025 Jun 26;2(7):AIdbp2401120. link
Sahashi Y, Vukadinovic M, Amrollahi F, Trivedi H, Rhee J, Chen J, Cheng S, Ouyang D, Kwan AC. Opportunistic screening of chronic liver disease with deep-learning–enhanced echocardiography. NEJM AI. 2025 Feb 27;2(3):AIoa2400948. link
Hagopian R, Strebel T, Bernatz S, Myers GA, Offerman E, Zuniga E, Kim CY, Ng AT, Iwaz JA, Nürnberg L, Singh SP. AI Opportunistic Coronary Calcium Screening at Veterans Affairs Hospitals. NEJM AI. 2025 May 22;2(6):AIoa2400937. link
Curry N, Allen E, Silsby L, Goodacre S, Deane C, Deary A, Foster A, Griffiths J, Sharma R, Thomas H, Mischewitz S. Multicenter Double-Blind Study Evaluating AI-Driven Detection of Proximal Deep Vein Thrombosis. NEJM AI. 2025 Jan 23;2(2):AIoa2400741. link
Li J, Aguirre AD, Junior VM, Jin J, Liu C, Zhong L, Sun C, Clifford G, Brandon Westover M, Hong S. An Electrocardiogram Foundation Model Built on over 10 Million Recordings. NEJM AI. 2025 Jun 26;2(7):AIoa2401033. link
Zhang S, Xu Y, Usuyama N, Xu H, Bagga J, Tinn R, Preston S, Rao R, Wei M, Valluri N, Wong C. A multimodal biomedical foundation model trained from fifteen million image–text pairs. NEJM AI. 2025 Jan 1;2(1):AIoa2400640. link
Wu K, Wu E, Theodorou B, Liang W, Mack C, Glass L, Sun J, Zou J. Characterizing the clinical adoption of medical AI devices through US insurance claims. NEJM AI. 2024 Jan 1;1(1):AIoa2300030. link
Fajtl J, Welikala RA, Barman S, Chambers R, Bolter L, Anderson J, Olvera-Barrios A, Shakespeare R, Egan C, Owen CG, Tufail A. Trustworthy evaluation of clinical AI for analysis of medical images in diverse populations. NEJM AI. 2024 Aug 22;1(9):AIoa2400353. link
Bhargava A, López-Espina C, Schmalz L, Khan S, Watson GL, Urdiales D, Updike L, Kurtzman N, Dagan A, Doodlesack A, Stenson BA. FDA-Authorized AI/ML Tool for Sepsis Prediction: Development and Validation. NEJM AI. 2024 Nov 27;1(12):AIoa2400867. link
Dippel J, Prenißl N, Hense J, Liznerski P, Winterhoff T, Schallenberg S, Kloft M, Buchstab O, Horst D, Alber M, Ruff L. Ai-based anomaly detection for clinical-grade histopathological diagnostics. NEJM AI. 2024 Oct 24;1(11):AIoa2400468. link
Kazemzadeh S, Kiraly AP, Nabulsi Z, Sanjase N, Maimbolwa M, Shuma B, Jamshy S, Chen C, Agharwal A, T. Lau C, Sellergren A. Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities. NEJM AI. 2024 Sep 26;1(10):AIoa2400018. link
Qiu J, Wu J, Wei H, Shi P, Zhang M, Sun Y, Li L, Liu H, Liu H, Hou S, Zhao Y. Development and validation of a multimodal multitask vision foundation model for generalist ophthalmic artificial intelligence. NEJM AI. 2024 Nov 27;1(12):AIoa2300221. link
Zhu H, Jiang Y, Cheng C, Wang J, Zhu L, Chen X, Feng K, Liu Y, Zhang L, Luo Q, He X. Four-Channel ECG as a Single Source for Early Diagnosis of Cardiac Hypertrophy and Dilation—A Deep Learning Approach. NEJM AI. 2024 Sep 26;1(10):AIoa2300297. link
Lin C, Liu WT, Chang CH, Lee CC, Hsing SC, Fang WH, Tsai DJ, Chen KC, Lee CH, Cheng CC, Hung YJ. Artificial intelligence–powered rapid identification of ST-elevation myocardial infarction via electrocardiogram (ARISE)—a pragmatic randomized controlled trial. NEJM AI. 2024 Jun 27;1(7):AIoa2400190. link
Tu T, Azizi S, Driess D, Schaekermann M, Amin M, Chang PC, Carroll A, Lau C, Tanno R, Ktena I, Palepu A. Towards generalist biomedical AI. Nejm Ai. 2024 Feb 22;1(3):AIoa2300138. link
Dagan N, Magen O, Leshchinsky M, Makov-Assif M, Lipsitch M, Reis BY, Yaron S, Netzer D, Balicer RD. Prospective evaluation of machine learning for public health screening: identifying unknown hepatitis C carriers. NEJM AI. 2024 Jan 25;1(2):AIoa2300012. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Honkamaa J, Khan U, Koivukoski S, Valkonen M, Latonen L, Ruusuvuori P, Marttinen P. Deformation equivariant cross-modality image synthesis with paired non-aligned training data. Medical Image Analysis. 2023 Dec 1;90:102940. link
Lin L, Peng L, He H, Cheng P, Wu J, Wong KK, Tang X. Yolocurvseg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation. Medical Image Analysis. 2023 Dec 1;90:102937. link
Ostmeier S, Axelrod B, Isensee F, Bertels J, Mlynash M, Christensen S, Lansberg MG, Albers GW, Sheth R, Verhaaren BF, Mahammedi A. USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging. Medical Image Analysis. 2023 Dec 1;90:102927. link
Li X, Liang X, Luo G, Wang W, Wang K, Li S. Ambiguity-aware breast tumor cellularity estimation via self-ensemble label distribution learning. Medical Image Analysis. 2023 Dec 1;90:102944. link
Bobrow TL, Golhar M, Vijayan R, Akshintala VS, Garcia JR, Durr NJ. Colonoscopy 3D video dataset with paired depth from 2D-3D registration. Medical image analysis. 2023 Dec 1;90:102956. link
Zhang M, Wu Y, Zhang H, Qin Y, Zheng H, Tang W, Arnold C, Pei C, Yu P, Nan Y, Yang G. Multi-site, multi-domain airway tree modeling. Medical image analysis. 2023 Dec 1;90:102957. link
Yu X, Yang Q, Zhou Y, Cai LY, Gao R, Lee HH, Li T, Bao S, Xu Z, Lasko TA, Abramson RG. Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation. Medical Image Analysis. 2023 Dec 1;90:102939. link
Xu X, Jia Q, Yuan H, Qiu H, Dong Y, Xie W, Yao Z, Zhang J, Nie Z, Li X, Shi Y. A clinically applicable AI system for diagnosis of congenital heart diseases based on computed tomography images. Medical Image Analysis. 2023 Dec 1;90:102953. link
Andrearczyk V, Oreiller V, Boughdad S, Le Rest CC, Tankyevych O, Elhalawani H, Jreige M, Prior JO, Vallières M, Visvikis D, Hatt M. Automatic head and neck tumor segmentation and outcome prediction relying on FDG-PET/CT images: findings from the second edition of the HECKTOR challenge. Medical image analysis. 2023 Dec 1;90:102972. link
Chen Y, Guo X, Pan Y, Xia Y, Yuan Y. Dynamic feature splicing for few-shot rare disease diagnosis. Medical Image Analysis. 2023 Dec 1;90:102959. link
Fan Z, Gong P, Tang S, Lee CU, Zhang X, Song P, Chen S, Li H. Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework. Medical image analysis. 2023 Dec 1;90:102960. link
Gaillochet M, Desrosiers C, Lombaert H. Active learning for medical image segmentation with stochastic batches. Medical Image Analysis. 2023 Dec 1;90:102958. link
Kascenas A, Sanchez P, Schrempf P, Wang C, Clackett W, Mikhael SS, Voisey JP, Goatman K, Weir A, Pugeault N, Tsaftaris SA. The role of noise in denoising models for anomaly detection in medical images. Medical image analysis. 2023 Dec 1;90:102963. link
Wang AQ, Evan MY, Dalca AV, Sabuncu MR. A robust and interpretable deep learning framework for multi-modal registration via keypoints. Medical image analysis. 2023 Dec 1;90:102962. link
Gu Y, Otake Y, Uemura K, Soufi M, Takao M, Talbot H, Okada S, Sugano N, Sato Y. Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography. Medical Image Analysis. 2023 Dec 1;90:102970. link
Zhao H, Zheng Q, Teng C, Yasrab R, Drukker L, Papageorghiou AT, Noble JA. Memory-based unsupervised video clinical quality assessment with multi-modality data in fetal ultrasound. Medical Image Analysis. 2023 Dec 1;90:102977. link
de Vries L, van Herten RL, Hoving JW, Išgum I, Emmer BJ, Majoie CB, Marquering HA, Gavves E. Spatio-temporal physics-informed learning: A novel approach to CT perfusion analysis in acute ischemic stroke. Medical image analysis. 2023 Dec 1;90:102971. link
Graham MS, Tudosiu PD, Wright P, Pinaya WH, Teikari P, Patel A, Jean-Marie U, Mah YH, Teo JT, Jäger HR, Werring D. Latent Transformer Models for out-of-distribution detection. Medical Image Analysis. 2023 Dec 1;90:102967. link
Pizarro R, Assemlal HE, Jegathambal SK, Jubault T, Antel S, Arnold D, Shmuel A. Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images. Medical Image Analysis. 2023 Dec 1;90:102942. link
Park H, Li B, Liu Y, Nelson MS, Wilson HM, Sifakis E, Eliceiri KW. Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation. Medical image analysis. 2023 Dec 1;90:102961. link
Beetz M, Banerjee A, Ossenberg-Engels J, Grau V. Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images. Medical Image Analysis. 2023 Dec 1;90:102975. link
Xu C, Song Y, Zhang D, Bittencourt LK, Tirumani SH, Li S. Spatiotemporal knowledge teacher–student reinforcement learning to detect liver tumors without contrast agents. Medical Image Analysis. 2023 Dec 1;90:102980. link
La Barbera G, Rouet L, Boussaid H, Lubet A, Kassir R, Sarnacki S, Gori P, Bloch I. Tubular structures segmentation of pediatric abdominal-visceral ceCT images with renal tumors: assessment, comparison and improvement. Medical Image Analysis. 2023 Dec 1;90:102986. link
Zhou B, Xie H, Liu Q, Chen X, Guo X, Feng Z, Hou J, Zhou SK, Li B, Rominger A, Shi K. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical image analysis. 2023 Dec 1;90:102993. link
Tian Y, Liu F, Pang G, Chen Y, Liu Y, Verjans JW, Singh R, Carneiro G. Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. Medical image analysis. 2023 Dec 1;90:102930. link
He W, Zhang C, Dai J, Liu L, Wang T, Liu X, Jiang Y, Li N, Xiong J, Wang L, Xie Y. A statistical deformation model-based data augmentation method for volumetric medical image segmentation. Medical image analysis. 2024 Jan 1;91:102984. link
Shahin AH, Zhao A, Whitehead AC, Alexander DC, Jacob J, Barber D. CenTime: Event-conditional modelling of censoring in survival analysis. Medical Image Analysis. 2024 Jan 1;91:103016. link
Liu B, Dolz J, Galdran A, Kobbi R, Ayed IB. Do we really need dice? the hidden region-size biases of segmentation losses. Medical Image Analysis. 2024 Jan 1;91:103015. link
Adiga S, Dolz J, Lombaert H. Anatomically-aware uncertainty for semi-supervised image segmentation. Medical Image Analysis. 2024 Jan 1;91:103011. link
Islam NU, Zhou Z, Gehlot S, Gotway MB, Liang J. Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism. Medical image analysis. 2024 Jan 1;91:102988. link
Wang Y, Luo Y, Zu C, Zhan B, Jiao Z, Wu X, Zhou J, Shen D, Zhou L. 3D multi-modality Transformer-GAN for high-quality PET reconstruction. Medical Image Analysis. 2024 Jan 1;91:102983. link
Liu P, Ji L, Ye F, Fu B. Advmil: Adversarial multiple instance learning for the survival analysis on whole-slide images. Medical Image Analysis. 2024 Jan 1;91:103020. link
Park S, Lee ES, Shin KS, Lee JE, Ye JC. Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology. Medical Image Analysis. 2024 Jan 1;91:103021. link
Xie Y, Zhang J, Liu L, Wang H, Ye Y, Verjans J, Xia Y. ReFs: A hybrid pre-training paradigm for 3D medical image segmentation. Medical Image Analysis. 2024 Jan 1;91:103023. link
Chen Z, Du Y, Hu J, Liu Y, Li G, Wan X, Chang TH. Mapping medical image-text to a joint space via masked modeling. Medical Image Analysis. 2024 Jan 1;91:103018. link
Fischer M, Bartler A, Yang B. Prompt tuning for parameter-efficient medical image segmentation. Medical Image Analysis. 2024 Jan 1;91:103024. link
Chen Z, Du Y, Hu J, Liu Y, Li G, Wan X, Chang TH. Mapping medical image-text to a joint space via masked modeling. Medical Image Analysis. 2024 Jan 1;91:103018. link
Fischer M, Bartler A, Yang B. Prompt tuning for parameter-efficient medical image segmentation. Medical Image Analysis. 2024 Jan 1;91:103024. link
Kim B, Oh Y, Wood BJ, Summers RM, Ye JC. C-DARL: Contrastive diffusion adversarial representation learning for label-free blood vessel segmentation. Medical Image Analysis. 2024 Jan 1;91:103022. link
Chen B, Zhang Z, Xia D, Sidky EY, Pan X. Prototyping optimization-based image reconstructions from limited-angular-range data in dual-energy CT. Medical Image Analysis. 2024 Jan 1;91:103025. link
Tiwary P, Bhattacharyya K, Prathosh AP. Cycle consistent twin energy-based models for image-to-image translation. Medical Image Analysis. 2024 Jan 1;91:103031. link
Sudre CH, Van Wijnen K, Dubost F, Adams H, Atkinson D, Barkhof F, Birhanu MA, Bron EE, Camarasa R, Chaturvedi N, Chen Y. Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021. Medical Image Analysis. 2024 Jan 1;91:103029. link
Li W, Zhang Y, Zhou H, Yang W, Xie Z, He Y. CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation. Medical Image Analysis. 2025 Feb 1;100:103404. link
Zhong S, Wang W, Feng Q, Zhang Y, Ning Z. Cross-view discrepancy-dependency network for volumetric medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103329. link
Khaledian N, Villard PF, Hammer PE, Perrin DP, Berger MO. Image-based simulation of mitral valve dynamic closure including anisotropy. Medical Image Analysis. 2025 Jan 1;99:103323. link
Manigrasso F, Milazzo R, Russo AS, Lamberti F, Strand F, Pagnani A, Morra L. Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures. Medical Image Analysis. 2025 Jan 1;99:103320. link
Jiang X, Zhang D, Li X, Liu K, Cheng KT, Yang X. Labeled-to-unlabeled distribution alignment for partially-supervised multi-organ medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103333. link
Huang J, Yang L, Wang F, Wu Y, Nan Y, Wu W, Wang C, Shi K, Aviles-Rivero AI, Schönlieb CB, Zhang D. Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba. Medical Image Analysis. 2025 Jan 1;99:103334. link
Płotka S, Szczepański T, Szenejko P, Korzeniowski P, Calvo JR, Khalil A, Shamshirsaz A, Brawura-Biskupski-Samaha R, Išgum I, Sánchez CI, Sitek A. Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome. Medical Image Analysis. 2025 Jan 1;99:103330. link
Wang CW, Firdi NP, Chu TC, Faiz MF, Iqbal MZ, Li Y, Yang B, Mallya M, Bashashati A, Li F, Wang H. ATEC23 Challenge: Automated prediction of treatment effectiveness in ovarian cancer using histopathological images. Medical Image Analysis. 2025 Jan 1;99:103342. link
Lee W, Wagner F, Galdran A, Shi Y, Xia W, Wang G, Mou X, Ahamed MA, Imran AA, Oh JE, Kim K. Low-dose computed tomography perceptual image quality assessment. Medical Image Analysis. 2025 Jan 1;99:103343. link
Chen S, Garcia-Uceda A, Su J, van Tulder G, Wolff L, van Walsum T, de Bruijne M. Label refinement network from synthetic error augmentation for medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103355. link
Gu Y, Sun Z, Chen T, Xiao X, Liu Y, Xu Y, Najman L. Dual structure-aware image filterings for semi-supervised medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103364. link
Zhao C, Esposito M, Xu Z, Zhou W. HAGMN-UQ: Hyper association graph matching network with uncertainty quantification for coronary artery semantic labeling. Medical image analysis. 2025 Jan 1;99:103374. link
Xie K, Yang J, Wei D, Weng Z, Fua P. Efficient anatomical labeling of pulmonary tree structures via deep point-graph representation-based implicit fields. Medical image analysis. 2025 Jan 1;99:103367. link
Lei W, Xu W, Li K, Zhang X, Zhang S. MedLSAM: Localize and segment anything model for 3D CT images. Medical Image Analysis. 2025 Jan 1;99:103370. link
Wang F, Zou Z, Sakla N, Partyka L, Rawal N, Singh G, Zhao W, Ling H, Huang C, Prasanna P, Chen C. TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs. Medical Image Analysis. 2025 Jan 1;99:103373. link
Banduc T, Azzolin L, Manninger M, Scherr D, Plank G, Pezzuto S, Costabal FS. Simulation-free prediction of atrial fibrillation inducibility with the fibrotic kernel signature. Medical Image Analysis. 2025 Jan 1;99:103375. link
Lang W, Liu Z, Zhang Y. DACG: Dual Attention and Context Guidance model for radiology report generation. Medical Image Analysis. 2025 Jan 1;99:103377. link
Ma Q, Kaladji A, Shu H, Yang G, Lucas A, Haigron P. Beyond strong labels: Weakly-supervised learning based on Gaussian pseudo labels for the segmentation of ellipse-like vascular structures in non-contrast CTs. Medical Image Analysis. 2025 Jan 1;99:103378. link
Mao Y, Feng Q, Zhang Y, Ning Z. Semantics and instance interactive learning for labeling and segmentation of vertebrae in CT images. Medical Image Analysis. 2025 Jan 1;99:103380. link
Mei L, Deng K, Cui Z, Fang Y, Li Y, Lai H, Tonetti MS, Shen D. Clinical knowledge-guided hybrid classification network for automatic periodontal disease diagnosis in X-ray image. Medical Image Analysis. 2025 Jan 1;99:103376. link
Zhang Z, Keles E, Durak G, Taktak Y, Susladkar O, Gorade V, Jha D, Ormeci AC, Medetalibeyoglu A, Yao L, Wang B. Large-scale multi-center CT and MRI segmentation of pancreas with deep learning. Medical image analysis. 2025 Jan 1;99:103382. link
Lanfredi RB, Mukherjee P, Summers RM. Enhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification. Medical Image Analysis. 2025 Jan 1;99:103383. link
Tang S, Yan S, Qi X, Gao J, Ye M, Zhang J, Zhu X. Few-shot medical image segmentation with high-fidelity prototypes. Medical Image Analysis. 2025 Feb 1;100:103412. link
Wang KN, Wang H, Zhou GQ, Wang Y, Yang L, Chen Y, Li S. TSdetector: Temporal–Spatial self-correction collaborative learning for colonoscopy video detection. Medical Image Analysis. 2025 Feb 1;100:103384. link
Xie H, Guo L, Velo A, Liu Z, Liu Q, Guo X, Zhou B, Chen X, Tsai YJ, Miao T, Xia M. Noise-aware dynamic image denoising and positron range correction for Rubidium-82 cardiac PET imaging via self-supervision. Medical Image Analysis. 2025 Feb 1;100:103391. link
Camps J, Wang ZJ, Doste R, Berg LA, Holmes M, Lawson B, Tomek J, Burrage K, Bueno-Orovio A, Rodriguez B. Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing. Medical Image Analysis. 2025 Feb 1;100:103361. link
Zhong L, Xiao R, Shu H, Zheng K, Li X, Wu Y, Ma J, Feng Q, Yang W. NCCT-to-CECT synthesis with contrast-enhanced knowledge and anatomical perception for multi-organ segmentation in non-contrast CT images. Medical Image Analysis. 2025 Feb 1;100:103397. link
Wang W, Xia Q, Yan Z, Hu Z, Chen Y, Zheng W, Wang X, Nie S, Metaxas D, Zhang S. AVDNet: joint coronary artery and vein segmentation with topological consistency. Medical Image Analysis. 2024 Jan 1;91:102999. link
Zhang S, Metaxas D. On the challenges and perspectives of foundation models for medical image analysis. Medical image analysis. 2024 Jan 1;91:102996. link
Dai J, Liu T, Torigian DA, Tong Y, Han S, Nie P, Zhang J, Li R, Xie F, Udupa JK. GA-Net: A geographical attention neural network for the segmentation of body torso tissue composition. Medical image analysis. 2024 Jan 1;91:102987. link
Peng J, Wang P, Pedersoli M, Desrosiers C. Boundary-aware information maximization for self-supervised medical image segmentation. Medical Image Analysis. 2024 May 1;94:103150. link
Chen L, Bentley P, Mori K, Misawa K, Fujiwara M, Rueckert D. Self-supervised learning for medical image analysis using image context restoration. Medical image analysis. 2019 Dec 1;58:101539. link
Freitas J, Gomes-Fonseca J, Tonelli AC, Correia-Pinto J, Fonseca JC, Queirós S. Automatic multi-view pose estimation in focused cardiac ultrasound. Medical Image Analysis. 2024 May 1;94:103146. link
Lyu J, Wang S, Tian Y, Zou J, Dong S, Wang C, Aviles-Rivero AI, Qin J. STADNet: Spatial-temporal attention-guided dual-path network for cardiac cine MRI super-resolution. Medical Image Analysis. 2024 May 1;94:103142. link
Gut D, Trombini M, Kucybała I, Krupa K, Rozynek M, Dellepiane S, Tabor Z, Wojciechowski W. Use of superpixels for improvement of inter-rater and intra-rater reliability during annotation of medical images. Medical Image Analysis. 2024 May 1;94:103141. link
Camps J, Berg LA, Wang ZJ, Sebastian R, Riebel LL, Doste R, Zhou X, Sachetto R, Coleman J, Lawson B, Grau V. Digital twinning of the human ventricular activation sequence to clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials. Medical Image Analysis. 2024 May 1;94:103108. link
Schmidt A, Mohareri O, DiMaio S, Yip MC, Salcudean SE. Tracking and mapping in medical computer vision: A review. Medical Image Analysis. 2024 May 1;94:103131. link
Zhu Z, Ma X, Wang W, Dong S, Wang K, Wu L, Luo G, Wang G, Li S. Boosting knowledge diversity, accuracy, and stability via tri-enhanced distillation for domain continual medical image segmentation. Medical image analysis. 2024 May 1;94:103112. link
Berenguer AD, Kvasnytsia M, Bossa MN, Mukherjee T, Deligiannis N, Sahli H. Semi-supervised medical image classification via distance correlation minimization and graph attention regularization. Medical image analysis. 2024 May 1;94:103107. link
Su J, Luo Z, Lian S, Lin D, Li S. Mutual learning with reliable pseudo label for semi-supervised medical image segmentation. Medical Image Analysis. 2024 May 1;94:103111. link
Chen W, Zhao W, Chen Z, Liu T, Liu L, Liu J, Yuan Y. Mask-aware transformer with structure invariant loss for CT translation. Medical Image Analysis. 2024 Aug 1;96:103205. link
Mo Y, Liu F, Yang G, Wang S, Zheng J, Wu F, Papież BW, McIlwraith D, He T, Guo Y. Labelling with dynamics: A data-efficient learning paradigm for medical image segmentation. Medical Image Analysis. 2024 Jul 1;95:103196. link
Schmidt K, Bearce B, Chang K, Coombs L, Farahani K, Elbatel M, Mouheb K, Marti R, Zhang R, Zhang Y, Wang Y. Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge. Medical Image Analysis. 2024 Jul 1;95:103206. link
Zhu W, Jin Y, Ma G, Chen G, Egger J, Zhang S, Metaxas DN. Classification of lung cancer subtypes on CT images with synthetic pathological priors. Medical Image Analysis. 2024 Jul 1;95:103199. link
Martín-Saladich Q, Pericàs JM, Ciudin A, Ramirez-Serra C, Escobar M, Rivera-Esteban J, Aguadé-Bruix S, Ballester MA, Herance JR. Metabolic-associated fatty liver voxel-based quantification on CT images using a contrast adapted automatic tool. Medical Image Analysis. 2024 Jul 1;95:103185. link
Meng Y, Zhang Y, Xie J, Duan J, Joddrell M, Madhusudhan S, Peto T, Zhao Y, Zheng Y. Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment. Medical Image Analysis. 2024 Jul 1;95:103183. link
Liu Q, Tsai YJ, Gallezot JD, Guo X, Chen MK, Pucar D, Young C, Panin V, Casey M, Miao T, Xie H. Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification. Medical Image Analysis. 2024 Jul 1;95:103180. link
Stan S, Rostami M. Unsupervised model adaptation for source-free segmentation of medical images. Medical Image Analysis. 2024 Jul 1;95:103179. link
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu YH, Palyo R, Miller EJ, Sinusas AJ, Staib L. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis. 2024 Aug 1;96:103190. link
Chen Y, Liu Y, Wang C, Elliott M, Kwok CF, Peña-Solorzano C, Tian Y, Liu F, Frazer H, McCarthy DJ, Carneiro G. BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations. Medical image analysis. 2024 Aug 1;96:103192. link
Jiao J, Zhou J, Li X, Xia M, Huang Y, Huang L, Wang N, Zhang X, Zhou S, Wang Y, Guo Y. Usfm: A universal ultrasound foundation model generalized to tasks and organs towards label efficient image analysis. Medical image analysis. 2024 Aug 1;96:103202. link
D‘Souza NS, Wang H, Giovannini A, Foncubierta-Rodriguez A, Beck KL, Boyko O, Syeda-Mahmood TF. Fusing modalities by multiplexed graph neural networks for outcome prediction from medical data and beyond. Medical Image Analysis. 2024 Apr 1;93:103064. link
Harnod Z, Lin C, Yang HW, Wang ZW, Huang HL, Lin TY, Huang CY, Lin LY, Young HW, Lo MT. A transferable in-silico augmented ischemic model for virtual myocardial perfusion imaging and myocardial infarction detection. Medical Image Analysis. 2024 Apr 1;93:103087. link
Pankewitz LR, Hustad KG, Govil S, Perry JC, Hegde S, Tang R, Omens JH, Young AA, McCulloch AD, Arevalo HJ. A universal biventricular coordinate system incorporating valve annuli: Validation in congenital heart disease. Medical image analysis. 2024 Apr 1;93:103091. link
Sun J, Wei D, Wang L, Zheng Y. Hybrid unsupervised representation learning and pseudo-label supervised self-distillation for rare disease imaging phenotype classification with dispersion-aware imbalance correction. Medical Image Analysis. 2024 Apr 1;93:103102. link
Chen X, Zhou B, Xie H, Guo X, Zhang J, Duncan JS, Miller EJ, Sinusas AJ, Onofrey JA, Liu C. DuSFE: Dual-Channel Squeeze-Fusion-Excitation co-attention for cross-modality registration of cardiac SPECT and CT. Medical image analysis. 2023 Aug 1;88:102840. link
Ferdian E, Marlevi D, Schollenberger J, Aristova M, Edelman ER, Schnell S, Figueroa CA, Nordsletten DA, Young AA. Cerebrovascular super-resolution 4D Flow MRI–Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure. Medical Image Analysis. 2023 Aug 1;88:102831. link
Huttinga NR, Bruijnen T, van den Berg CA, Sbrizzi A. Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy. Medical Image Analysis. 2023 Aug 1;88:102843. link
Khor HG, Ning G, Sun Y, Lu X, Zhang X, Liao H. Anatomically constrained and attention-guided deep feature fusion for joint segmentation and deformable medical image registration. Medical Image Analysis. 2023 Aug 1;88:102811. link
Xu K, Li T, Khan MS, Gao R, Antic SL, Huo Y, Sandler KL, Maldonado F, Landman BA. Body composition assessment with limited field-of-view computed tomography: A semantic image extension perspective. Medical image analysis. 2023 Aug 1;88:102852. link
Dawood T, Chen C, Sidhu BS, Ruijsink B, Gould J, Porter B, Elliott MK, Mehta V, Rinaldi CA, Puyol-Antón E, Razavi R. Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images. Medical Image Analysis. 2023 Aug 1;88:102861. link
Liu X, Prince JL, Xing F, Zhuo J, Reese T, Stone M, El Fakhri G, Woo J. Attentive continuous generative self-training for unsupervised domain adaptive medical image translation. Medical image analysis. 2023 Aug 1;88:102851. link
Li L, Ding W, Huang L, Zhuang X, Grau V. Multi-modality cardiac image computing: A survey. Medical image analysis. 2023 Aug 1;88:102869. link
Messaoudi H, Belaid A, Salem DB, Conze PH. Cross-dimensional transfer learning in medical image segmentation with deep learning. Medical image analysis. 2023 Aug 1;88:102868. link
Xu Z, Wang Y, Lu D, Luo X, Yan J, Zheng Y, Tong RK. Ambiguity-selective consistency regularization for mean-teacher semi-supervised medical image segmentation. Medical Image Analysis. 2023 Aug 1;88:102880. link
Xu X, Chen Y, Wu J, Lu J, Ye Y, Huang Y, Dou X, Li K, Wang G, Zhang S, Gong W. A novel one-to-multiple unsupervised domain adaptation framework for abdominal organ segmentation. Medical Image Analysis. 2023 Aug 1;88:102873. link
Xing X, Chen Z, Hou Y, Yuan Y. Gradient modulated contrastive distillation of low-rank multi-modal knowledge for disease diagnosis. Medical image analysis. 2023 Aug 1;88:102874. link
Chaitanya K, Erdil E, Karani N, Konukoglu E. Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation. Medical image analysis. 2023 Jul 1;87:102792. link
Bahadormanesh N, Tomka B, Kadem M, Khodaei S, Keshavarz-Motamed Z. An ultrasound-exclusive non-invasive computational diagnostic framework for personalized cardiology of aortic valve stenosis. Medical Image Analysis. 2023 Jul 1;87:102795. link
Aggarwal A, Mortensen P, Hao J, Kaczmarczyk Ł, Cheung AT, Al Ghofaily L, Gorman RC, Desai ND, Bavaria JE, Pouch AM. Strain estimation in aortic roots from 4D echocardiographic images using medial modeling and deformable registration. Medical image analysis. 2023 Jul 1;87:102804. link
Li L, Wu F, Wang S, Luo X, Martín-Isla C, Zhai S, Zhang J, Liu Y, Zhang Z, Ankenbrand MJ, Jiang H. MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images. Medical Image Analysis. 2023 Jul 1;87:102808. link
Murugesan B, Liu B, Galdran A, Ayed IB, Dolz J. Calibrating segmentation networks with margin-based label smoothing. Medical Image Analysis. 2023 Jul 1;87:102826. link
Xia Y, Ravikumar N, Lassila T, Frangi AF. Virtual high-resolution MR angiography from non-angiographic multi-contrast MRIs: synthetic vascular model populations for in-silico trials. Medical Image Analysis. 2023 Jul 1;87:102814. link
Gao H, Lyu M, Zhao X, Yang F, Bai X. Contour-aware network with class-wise convolutions for 3D abdominal multi-organ segmentation. Medical Image Analysis. 2023 Jul 1;87:102838. link
Li W, Zhang Y, Zhou H, Yang W, Xie Z, He Y. CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation. Medical Image Analysis. 2025 Feb 1;100:103404. link
Zhong S, Wang W, Feng Q, Zhang Y, Ning Z. Cross-view discrepancy-dependency network for volumetric medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103329. link
Khaledian N, Villard PF, Hammer PE, Perrin DP, Berger MO. Image-based simulation of mitral valve dynamic closure including anisotropy. Medical Image Analysis. 2025 Jan 1;99:103323. link
Manigrasso F, Milazzo R, Russo AS, Lamberti F, Strand F, Pagnani A, Morra L. Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures. Medical Image Analysis. 2025 Jan 1;99:103320. link
Jiang X, Zhang D, Li X, Liu K, Cheng KT, Yang X. Labeled-to-unlabeled distribution alignment for partially-supervised multi-organ medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103333. link
Huang J, Yang L, Wang F, Wu Y, Nan Y, Wu W, Wang C, Shi K, Aviles-Rivero AI, Schoenlieb CB, Zhang D. Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba. Medical Image Analysis. 2025 Jan 1;99:103334. link
Lee W, Wagner F, Galdran A, Shi Y, Xia W, Wang G, Mou X, Ahamed MA, Imran AA, Oh JE, Kim K. Low-dose computed tomography perceptual image quality assessment. Medical Image Analysis. 2025 Jan 1;99:103343. link
Chen S, Garcia-Uceda A, Su J, van Tulder G, Wolff L, van Walsum T, de Bruijne M. Label refinement network from synthetic error augmentation for medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103355. link
Gu Y, Sun Z, Chen T, Xiao X, Liu Y, Xu Y, Najman L. Dual structure-aware image filterings for semi-supervised medical image segmentation. Medical Image Analysis. 2025 Jan 1;99:103364. link
Zhao C, Esposito M, Xu Z, Zhou W. HAGMN-UQ: Hyper association graph matching network with uncertainty quantification for coronary artery semantic labeling. Medical image analysis. 2025 Jan 1;99:103374. link
Xie K, Yang J, Wei D, Weng Z, Fua P. Efficient anatomical labeling of pulmonary tree structures via deep point-graph representation-based implicit fields. Medical image analysis. 2025 Jan 1;99:103367. link
Lei W, Xu W, Li K, Zhang X, Zhang S. MedLSAM: Localize and segment anything model for 3D CT images. Medical Image Analysis. 2025 Jan 1;99:103370. link
Banduc T, Azzolin L, Manninger M, Scherr D, Plank G, Pezzuto S, Costabal FS. Simulation-free prediction of atrial fibrillation inducibility with the fibrotic kernel signature. Medical Image Analysis. 2025 Jan 1;99:103375. link
Ma Q, Kaladji A, Shu H, Yang G, Lucas A, Haigron P. Beyond strong labels: Weakly-supervised learning based on Gaussian pseudo labels for the segmentation of ellipse-like vascular structures in non-contrast CTs. Medical Image Analysis. 2025 Jan 1;99:103378. link
Mao Y, Feng Q, Zhang Y, Ning Z. Semantics and instance interactive learning for labeling and segmentation of vertebrae in CT images. Medical Image Analysis. 2025 Jan 1;99:103380. link
Zhang Z, Keles E, Durak G, Taktak Y, Susladkar O, Gorade V, Jha D, Ormeci AC, Medetalibeyoglu A, Yao L, Wang B. Large-scale multi-center CT and MRI segmentation of pancreas with deep learning. Medical image analysis. 2025 Jan 1;99:103382. link
Xie H, Guo L, Velo A, Liu Z, Liu Q, Guo X, Zhou B, Chen X, Tsai YJ, Miao T, Xia M. Noise-aware dynamic image denoising and positron range correction for Rubidium-82 cardiac PET imaging via self-supervision. Medical Image Analysis. 2025 Feb 1;100:103391. link
Camps J, Wang ZJ, Doste R, Berg LA, Holmes M, Lawson B, Tomek J, Burrage K, Bueno-Orovio A, Rodriguez B. Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing. Medical Image Analysis. 2025 Feb 1;100:103361. link
Zhong L, Xiao R, Shu H, Zheng K, Li X, Wu Y, Ma J, Feng Q, Yang W. NCCT-to-CECT synthesis with contrast-enhanced knowledge and anatomical perception for multi-organ segmentation in non-contrast CT images. Medical Image Analysis. 2025 Feb 1;100:103397. link
Sun L, Han B, Jiang W, Liu W, Liu B, Tao D, Yu Z, Li C. Multi-scale region selection network in deep features for full-field mammogram classification. Medical Image Analysis. 2025 Feb 1;100:103399. link
Li W, Zhang Y, Zhou H, Yang W, Xie Z, He Y. CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation. Medical Image Analysis. 2025 Feb 1;100:103404. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Zeng Q, Xie Y, Lu Z, Lu M, Zhang J, Zhou Y, Xia Y. Consistency-guided differential decoding for enhancing semi-supervised medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Aug 1. link
Liu J, Li H, Zeng B, Wang H, Kikinis R, Joskowicz L, Chen X. An end-to-end geometry-based pipeline for automatic preoperative surgical planning of pelvic fracture reduction and fixation. IEEE Transactions on Medical Imaging. 2024 Jul 16. link
Ye Y, Zhang J, Chen Z, Xia Y. CADS: A self-supervised learner via cross-modal alignment and deep self-distillation for CT volume segmentation. IEEE Transactions on Medical Imaging. 2024 Jul 22. link
Quan Q, Yao Q, Zhu H, Zhou SK. IGU-Aug: Information-guided unsupervised augmentation and pixel-wise contrastive learning for medical image analysis. IEEE Transactions on Medical Imaging. 2024 Aug 1. link
Kim B, Zhuang Y, Mathai TS, Summers RM. OTMorph: Unsupervised Multi-domain Abdominal Medical Image Registration Using Neural Optimal Transport. IEEE Transactions on Medical Imaging. 2024 Aug 2. link
Xu Z, Liu Y, Xu G, Lukasiewicz T. Self-supervised medical image segmentation using deep reinforced adaptive masking. IEEE Transactions on Medical Imaging. 2024 Aug 1. link
Chen M, Bian Y, Chen N, Qiu A. Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach. IEEE Transactions on Medical Imaging. 2024 Jul 30. link
Müller P, Meissen F, Kaissis G, Rueckert D. Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling. IEEE Transactions on Medical Imaging. 2024 Jul 29. link
Yang X, Xu L, Yu S, Xia Q, Li H, Zhang S. Segmentation and vascular vectorization for coronary artery by geometry-based cascaded neural network. IEEE Transactions on Medical Imaging. 2024 Jul 30. link
Zhang S, Shen X, Chen X, Yu Z, Ren B, Yang H, Zhang XY, Zhou Y. CQformer: Learning Dynamics Across Slices in Medical Image Segmentation. IEEE Transactions on Medical Imaging. 2024 Oct 10. link
Zhang J, Huang C, Lok UW, Dong Z, Liu H, Gong P, Song P, Chen S. Enhancing Row-column array (RCA)-based 3D ultrasound vascular imaging with spatial-temporal similarity weighting. IEEE transactions on medical imaging. 2024 Aug 6. link
Gao J, Lao Q, Kang Q, Liu P, Du C, Li K, Zhang L. Boosting your context by dual similarity checkup for in-context learning medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Aug 8. link
Zhang M, Hu X, Gu L, Liu L, Kobayashi K, Harada T, Yan Y, Summers RM, Zhu Y. A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images with Multi-Relationship Graph Learning. IEEE Transactions on Medical Imaging. 2024 Aug 9. link
Yan S, Yu Z, Liu C, Ju L, Mahapatra D, Betz-Stablein B, Mar V, Janda M, Soyer P, Ge Z. Prompt-driven latent domain generalization for medical image classification. IEEE Transactions on Medical Imaging. 2024 Aug 13. link
Valiuddin MA, Viviers CG, Van Sloun RJ, De With PH, van der Sommen F. Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging. IEEE Transactions on Medical Imaging. 2024 Aug 19. link
Xu C, Song Y, Zhang D, Bittencourt LK, Tirumani SH, Li S. Spatiotemporal knowledge teacher–student reinforcement learning to detect liver tumors without contrast agents. Medical Image Analysis. 2023 Dec 1;90:102980. link
La Barbera G, Rouet L, Boussaid H, Lubet A, Kassir R, Sarnacki S, Gori P, Bloch I. Tubular structures segmentation of pediatric abdominal-visceral ceCT images with renal tumors: assessment, comparison and improvement. Medical Image Analysis. 2023 Dec 1;90:102986. link
Zhou B, Xie H, Liu Q, Chen X, Guo X, Feng Z, Hou J, Zhou SK, Li B, Rominger A, Shi K. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical image analysis. 2023 Dec 1;90:102993. link
Tian Y, Liu F, Pang G, Chen Y, Liu Y, Verjans JW, Singh R, Carneiro G. Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. Medical image analysis. 2023 Dec 1;90:102930. link
He W, Zhang C, Dai J, Liu L, Wang T, Liu X, Jiang Y, Li N, Xiong J, Wang L, Xie Y. A statistical deformation model-based data augmentation method for volumetric medical image segmentation. Medical image analysis. 2024 Jan 1;91:102984. link
Shahin AH, Zhao A, Whitehead AC, Alexander DC, Jacob J, Barber D. CenTime: Event-conditional modelling of censoring in survival analysis. Medical Image Analysis. 2024 Jan 1;91:103016. link
Liu B, Dolz J, Galdran A, Kobbi R, Ayed IB. Do we really need dice? the hidden region-size biases of segmentation losses. Medical Image Analysis. 2024 Jan 1;91:103015. link
Adiga S, Dolz J, Lombaert H. Anatomically-aware uncertainty for semi-supervised image segmentation. Medical Image Analysis. 2024 Jan 1;91:103011. link
Islam NU, Zhou Z, Gehlot S, Gotway MB, Liang J. Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism. Medical image analysis. 2024 Jan 1;91:102988. link
Wang Y, Luo Y, Zu C, Zhan B, Jiao Z, Wu X, Zhou J, Shen D, Zhou L. 3D multi-modality Transformer-GAN for high-quality PET reconstruction. Medical Image Analysis. 2024 Jan 1;91:102983. link
Liu P, Ji L, Ye F, Fu B. Advmil: Adversarial multiple instance learning for the survival analysis on whole-slide images. Medical Image Analysis. 2024 Jan 1;91:103020. link
Park S, Lee ES, Shin KS, Lee JE, Ye JC. Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology. Medical Image Analysis. 2024 Jan 1;91:103021. link
Mahapatra D, Yepes AJ, Bozorgtabar B, Roy S, Ge Z, Reyes M. Multi-label generalized zero shot chest xray classification by combining image-text information with feature disentanglement. IEEE transactions on medical imaging. 2024 Jul 17. link
Zeng Q, Xie Y, Lu Z, Lu M, Zhang J, Xia Y. Consistency-guided differential decoding for enhancing semi-supervised medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Aug 1;44(1):44-56. link
Liu J, Li H, Zeng B, Wang H, Kikinis R, Joskowicz L, Chen X. An end-to-end geometry-based pipeline for automatic preoperative surgical planning of pelvic fracture reduction and fixation. IEEE Transactions on Medical Imaging. 2024 Jul 16. link
Ye Y, Zhang J, Chen Z, Xia Y. CADS: A self-supervised learner via cross-modal alignment and deep self-distillation for CT volume segmentation. IEEE Transactions on Medical Imaging. 2024 Jul 22. link
Quan Q, Yao Q, Zhu H, Zhou SK. IGU-Aug: Information-guided unsupervised augmentation and pixel-wise contrastive learning for medical image analysis. IEEE Transactions on Medical Imaging. 2024 Aug 1. link
Kim B, Zhuang Y, Mathai TS, Summers RM. Otmorph: unsupervised multi-domain abdominal medical image registration using neural optimal transport. IEEE Transactions on Medical Imaging. 2024 Aug 2. link
Xu Z, Liu Y, Xu G, Lukasiewicz T. Self-supervised medical image segmentation using deep reinforced adaptive masking. IEEE Transactions on Medical Imaging. 2024 Aug 1. link
Chen M, Bian Y, Chen N, Qiu A. Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach. IEEE Transactions on Medical Imaging. 2024 Jul 30. link
Müller P, Meissen F, Kaissis G, Rueckert D. Weakly supervised object detection in chest x-rays with differentiable roi proposal networks and soft roi pooling. IEEE Transactions on Medical Imaging. 2024 Jul 29. link
Yang X, Xu L, Yu S, Xia Q, Li H, Zhang S. Segmentation and vascular vectorization for coronary artery by geometry-based cascaded neural network. IEEE Transactions on Medical Imaging. 2024 Jul 30. link
Zhang S, Shen X, Chen X, Yu Z, Ren B, Yang H, Zhang XY, Zhou Y. Cqformer: Learning dynamics across slices in medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Oct 10. link
Zhang J, Huang C, Lok UW, Dong Z, Liu H, Gong P, Song P, Chen S. Enhancing Row-column array (RCA)-based 3D ultrasound vascular imaging with spatial-temporal similarity weighting. IEEE transactions on medical imaging. 2024 Aug 6. link
Gao J, Lao Q, Kang Q, Liu P, Du C, Li K, Zhang L. Boosting your context by dual similarity checkup for In-Context learning medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Aug 8. link
Zhang M, Hu X, Gu L, Liu L, Kobayashi K, Harada T, Yan Y, Summers RM, Zhu Y. A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images With Multi-Relationship Graph Learning. IEEE Transactions on Medical Imaging. 2024 Aug 9. link
Yan S, Yu Z, Liu C, Ju L, Mahapatra D, Betz-Stablein B, Mar V, Janda M, Soyer P, Ge Z. Prompt-driven latent domain generalization for medical image classification. IEEE Transactions on Medical Imaging. 2024 Aug 13. link
Valiuddin MA, Viviers CG, Van Sloun RJ, De With PH, van der Sommen F. Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging. IEEE Transactions on Medical Imaging. 2024 Aug 19. link
Chen Z, Bian Y, Shen E, Fan L, Zhu W, Shi F, Shao C, Chen X, Xiang D. Moment-consistent contrastive CycleGAN for cross-domain pancreatic image segmentation. IEEE Transactions on Medical Imaging. 2024 Aug 21. link
Kyung S, Won J, Pak S, Kim S, Lee S, Park K, Hong GS, Kim N. Generative adversarial network with robust discriminator through multi-task learning for low-dose ct denoising. IEEE Transactions on Medical Imaging. 2024 Aug 26. link
Liu C, Cheng S, Shi M, Shah A, Bai W, Arcucci R. Imitate: Clinical prior guided hierarchical vision-language pre-training. IEEE Transactions on Medical Imaging. 2024 Aug 26. link
Borazjani K, Khosravan N, Ying L, Hosseinalipour S. Multi-modal federated learning for cancer staging over non-iid datasets with unbalanced modalities. IEEE Transactions on Medical Imaging. 2024 Aug 28. link
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Yue Z, Jiang J, Hou W, Zhou Q, Spence JD, Fenster A, Qiu W, Ding M. Prior-knowledge embedded u-net based fully automatic vessel wall volume measurement of the carotid artery in 3d ultrasound image. IEEE Transactions on Medical Imaging. 2024 Sep 10. link
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Fu W, Hu H, Li X, Guo R, Chen T, Qian X. A Generalizable Causal-Invariance-Driven Segmentation Model for Peripancreatic Vessels. IEEE Transactions on Medical Imaging. 2024 May 13;43(11):3794-806. link
Lin J, Xie W, Kang L, Wu H. Dynamic-guided spatiotemporal attention for echocardiography video segmentation. IEEE Transactions on Medical Imaging. 2024 May 21;43(11):3843-55. link
Chen F, Han H, Wan P, Chen L, Kong W, Liao H, Wen B, Liu C, Zhang D. Do as sonographers think: Contrast-enhanced ultrasound for thyroid nodules diagnosis via microvascular infiltrative awareness. IEEE Transactions on Medical Imaging. 2024 May 27;43(11):3881-94. link
Geng H, Fan J, Yang S, Chen S, Xiao D, Ai D, Fu T, Song H, Yuan K, Duan F, Wang Y. DSC-Recon: Dual-Stage Complementary 4-D Organ Reconstruction From X-Ray Image Sequence for Intraoperative Fusion. IEEE Transactions on Medical Imaging. 2024 May 28;43(11):3909-23. link
Lu Y, Xu Z, Choi MH, Kim J, Jung SW. Cross-domain denoising for low-dose multi-frame spiral computed tomography. IEEE Transactions on Medical Imaging. 2024 May 24;43(11):3949-63. link
Ding S, Li J, Wang J, Ying S, Shi J. Multimodal co-attention fusion network with online data augmentation for cancer subtype classification. IEEE Transactions on Medical Imaging. 2024 May 27;43(11):3977-89. link
Wu Q, Chen Y, Liu W, Yue X, Zhuang X. Deep closing: Enhancing topological connectivity in medical tubular segmentation. IEEE Transactions on Medical Imaging. 2024 May 27;43(11):3990-4003. link
Yang Y, Yu J, Fu Z, Zhang K, Yu T, Wang X, Jiang H, Lv J, Huang Q, Han W. Token-mixer: Bind image and text in one embedding space for medical image reporting. IEEE Transactions on Medical Imaging. 2024 Jun 11;43(11):4017-28. link
Zhang Y, Li H, Gao Y, Duan H, Huang Y, Zheng Y. Prototype correlation matching and class-relation reasoning for few-shot medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Jun 11;43(11):4041-54. link
Li Z, Chang D, Zhang Z, Luo F, Liu Q, Zhang J, Yang G, Wu W. Dual-domain collaborative diffusion sampling for multi-source stationary computed tomography reconstruction. IEEE Transactions on Medical Imaging. 2024 Jun 28;43(10):3398-411. link
Xu K, Lu S, Huang B, Wu W, Liu Q. Stage-by-stage wavelet optimization refinement diffusion model for sparse-view CT reconstruction. IEEE Transactions on Medical Imaging. 2024 Jan 18;43(10):3412-24. link
Liu Y, Zhou X, Wei C, Xu Q. Sparse-view spectral CT reconstruction and material decomposition based on multi-channel SGM. IEEE Transactions on Medical Imaging. 2024 Jun 12;43(10):3425-35. link
Zhang J, Mao H, Wang X, Guo Y, Wu W. Wavelet-inspired multi-channel score-based model for limited-angle CT reconstruction. IEEE Transactions on Medical Imaging. 2024 Feb 19;43(10):3436-48. link
Wang Y, Li Z, Wu W. Time-reversion fast-sampling score-based model for limited-angle CT reconstruction. IEEE Transactions on Medical Imaging. 2024 Jun 24;43(10):3449-60. link
Wu W, Pan J, Wang Y, Wang S, Zhang J. Multi-channel optimization generative model for stable ultra-sparse-view CT reconstruction. IEEE Transactions on Medical Imaging. 2024 Mar 11;43(10):3461-75. link
Karageorgos GM, Zhang J, Peters N, Xia W, Niu C, Paganetti H, Wang G, De Man B. A denoising diffusion probabilistic model for metal artifact reduction in CT. IEEE Transactions on Medical Imaging. 2024 Jul 4;43(10):3521-32. link
Shi Y, Xia W, Wang G, Mou X. Blind ct image quality assessment using ddpm-derived content and transformer-based evaluator. IEEE Transactions on Medical Imaging. 2024 Jun 24;43(10):3559-69. link
Chen T, Wang C, Chen Z, Lei Y, Shan H. HiDiff: Hybrid diffusion framework for medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Jul 8. link
Wang K, Chen Z, Zhu M, Li Z, Weng J, Gu T. Score-based counterfactual generation for interpretable medical image classification and lesion localization. IEEE transactions on medical imaging. 2024 Mar 14;43(10):3596-607. link
Deshpande R, Özbey M, Li H, Anastasio MA, Brooks FJ. Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context. IEEE transactions on medical imaging. 2024 Jun 14;43(10):3608-20. link
Zhang Y, Li C, Zhong L, Chen Z, Yang W, Wang X. DoseDiff: distance-aware diffusion model for dose prediction in radiotherapy. IEEE Transactions on Medical Imaging. 2024 Apr 2;43(10):3621-33. link
Xu Y, Sun L, Peng W, Jia S, Morrison K, Perer A, Zandifar A, Visweswaran S, Eslami M, Batmanghelich K. MedSyn: text-guided anatomy-aware synthesis of high-fidelity 3-D CT images. IEEE Transactions on Medical Imaging. 2024 Jun 20;43(10):3648-60. link
Yin Y, Clark AR, Collins SL. 3D Single Vessel Fractional Moving Blood Volume (3D-svFMBV): Fully Automated Tissue Perfusion Estimation Using Ultrasound. IEEE Transactions on Medical Imaging. 2024 Mar 13;43(7):2707-17. link
Jang SI, Pan T, Li Y, Heidari P, Chen J, Li Q, Gong K. Spach Transformer: Spatial and channel-wise transformer based on local and global self-attentions for PET image denoising. IEEE transactions on medical imaging. 2023 Nov 23;43(6):2036-49. link
Penso C, Frenkel L, Goldberger J. Confidence calibration of a medical imaging classification system that is robust to label noise. IEEE Transactions on Medical Imaging. 2024 Jan 15;43(6):2050-60. link
Zhou C, Wang J, Xiang S, Liu F, Huang H, Qian D. A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images. IEEE Transactions on Medical Imaging. 2024 Jan 15;43(6):2086-97. link
Yang B, Gong K, Liu H, Li Q, Zhu W. Anatomically guided pet image reconstruction using conditional weakly-supervised multi-task learning integrating self-attention. IEEE Transactions on Medical Imaging. 2024 Jan 19;43(6):2098-112. link
Wang P, Zhang H, Zhu M, Jiang X, Qin J, Yuan Y. MGIML: Cancer grading with incomplete radiology-pathology data via memory learning and gradient homogenization. IEEE Transactions on Medical Imaging. 2024 Jan 17;43(6):2113-24. link
Wang H, He J, Cui H, Yuan B, Xia Y. Robust stochastic neural ensemble learning with noisy labels for thoracic disease classification. IEEE Transactions on Medical Imaging. 2024 Jan 24;43(6):2180-90. link
Cheng Z, Wang S, Xin T, Zhou T, Zhang H, Shao L. Few-shot medical image segmentation via generating multiple representative descriptors. IEEE Transactions on Medical Imaging. 2024 Jan 24;43(6):2202-14. link
Zhang Z, Yu C, Zhang H, Gao Z. Embedding tasks into the latent space: Cross-space consistency for multi-dimensional analysis in echocardiography. IEEE Transactions on Medical Imaging. 2024 Feb 8;43(6):2215-28. link
Guo Z, Tan Z, Feng J, Zhou J. 3D vascular segmentation supervised by 2D annotation of maximum intensity projection. IEEE Transactions on Medical Imaging. 2024 Feb 6;43(6):2241-53. link
Li K, Zhu Y, Yu L, Heng PA. A dual enrichment synergistic strategy to handle data heterogeneity for domain incremental cardiac segmentation. IEEE Transactions on Medical Imaging. 2024 Feb 12;43(6):2279-90. link
Zhou Q, Yu B, Xiao F, Ding M, Wang Z, Zhang X. Robust Semi-Supervised 3D Medical Image Segmentation With Diverse Joint-Task Learning and Decoupled Inter-Student Learning. IEEE Transactions on Medical Imaging. 2024 Feb 6;43(6):2317-31. link
Ren Z, Sidky EY, Barber RF, Kao CM, Pan X. Simultaneous activity and attenuation estimation in TOF-PET with TV-constrained nonconvex optimization. IEEE Transactions on Medical Imaging. 2024 Feb 14;43(6):2347-57. link
Onishi Y, Hashimoto F, Ote K, Ota R. Whole reconstruction-free system design for direct positron emission imaging from image generation to attenuation correction. IEEE Transactions on Medical Imaging. 2023 Dec 18;43(5):1654-63. link
Li X, Jing K, Yang Y, Wang Y, Ma J, Zheng H, Xu Z. Noise-generating and imaging mechanism inspired implicit regularization learning network for low dose ct reconstrution. IEEE Transactions on Medical Imaging. 2023 Dec 25;43(5):1677-89. link
He A, Li T, Yan J, Wang K, Fu H. Bilateral supervision network for semi-supervised medical image segmentation. IEEE Transactions on Medical Imaging. 2023 Dec 28;43(5):1715-26. link
Zhu J, Wang C, Zhang Y, Zhan M, Zhao W, Teng S, Lu L, Teng GJ. 3D/2D vessel registration based on Monte Carlo tree search and manifold regularization. IEEE Transactions on Medical Imaging. 2023 Dec 28;43(5):1727-39. link
Chen Y, Guo X, Xia Y, Yuan Y. Disentangle then calibrate with gradient guidance: A unified framework for common and rare disease diagnosis. IEEE Transactions on Medical Imaging. 2024 Jan 2;43(5):1816-27. link
Li Z, Gao Q, Wu Y, Niu C, Zhang J, Wang M, Wang G, Shan H. Quad-Net: Quad-domain network for CT metal artifact reduction. IEEE Transactions on Medical Imaging. 2024 Jan 9;43(5):1866-79. link
Chen Z, Niu C, Gao Q, Wang G, Shan H. LIT-Former: Linking in-plane and through-plane transformers for simultaneous CT image denoising and deblurring. IEEE Transactions on Medical Imaging. 2024 Jan 9;43(5):1880-94. link
Chen Q, Zhang J, Meng R, Zhou L, Li Z, Feng Q, Shen D. Modality-specific information disentanglement from multi-parametric MRI for breast tumor segmentation and computer-aided diagnosis. IEEE Transactions on Medical Imaging. 2024 Jan 11;43(5):1958-71. link
Chai Z, Luo L, Lin H, Heng PA, Chen H. Deep omni-supervised learning for rib fracture detection from chest radiology images. IEEE Transactions on Medical Imaging. 2024 Jan 12;43(5):1972-82. link
Liu H, Xu Z, Gao R, Li H, Wang J, Chabin G, Oguz I, Grbic S. Cosst: Multi-organ segmentation with partially labeled datasets using comprehensive supervisions and self-training. IEEE Transactions on Medical Imaging. 2024 Jan 15;43(5):1995-2009. link
Ta K, Ahn SS, Thorn SL, Stendahl JC, Zhang X, Langdon J, Staib LH, Sinusas AJ, Duncan JS. Multi-task learning for motion analysis and segmentation in 3D echocardiography. IEEE Transactions on Medical Imaging. 2024 Jan 17;43(5):2010-20. link
AI/DS and its applications in medicine/cardiovascular disease/breast cancer
Tan D, Hao R, Zhou X, Xia J, Su Y, Zheng C. A Novel Skip-Connection Strategy by Fusing Spatial and Channel Wise Features for Multi-Region Medical Image Segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 May 29. link
Chen H, Wang X, Li H, Wang L. 3D vessel segmentation with limited guidance of 2D structure-agnostic vessel annotations. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 4. link
Kang S, Kang Y, Tan S. Exploring and Exploiting Multi-modality Uncertainty for Tumor Segmentation on PET/CT. IEEE Journal of Biomedical and Health Informatics. 2024 May 22. link
Zhao W, Huang Z, Tang S, Li W, Gao Y, Hu Y, Fan W, Cheng C, Yang Y, Zheng H, Liang D. Mmca-net: a multimodal cross attention transformer network for nasopharyngeal carcinoma tumor segmentation based on a total-body PET/CT system. IEEE Journal of Biomedical and Health Informatics. 2024 May 28. link
Wang L, Wang L, Kuai Z, Tang L, Ou Y, Wu M, Shi T, Ye C, Zhu Y. Progressive dual priori network for generalized breast tumor segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 6. link
Hu J, Yang Y, Guo X, Wang J, Ma T. A Chebyshev Confidence Guided Source-Free Domain Adaptation Framework for Medical Image Segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 May 29. link
Liu J, Bilgi C, Bregasi A, Mitchell GF, Pahlevan NM. Noninvasive left ventricle pressure-volume loop determination method with cardiac magnetic resonance imaging and carotid tonometry using a physics-informed approach. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 11. link
Gunawan R, Tran Y, Zheng J, Nguyen H, Carrigan A, Mills MK, Chai R. Combining multistaged filters and modified segmentation network for improving lung nodules classification. IEEE Journal of Biomedical and Health Informatics. 2024 May 28. link
Tseng CH, Chien SJ, Wang PS, Lee SJ, Pu B, Zeng XJ. Real-time automatic m-mode echocardiography measurement with panel attention. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 12. link
Gravina M, Maddaluno M, Marrone S, Sansone M, Fusco R, Granata V, Petrillo A, Sansone C. A Physiological-Informed Generative Model for Improving Breast Lesion Classification in Small DCE-MRI Datasets. IEEE Journal of Biomedical and Health Informatics. 2024 Aug 14. link
Li Z, Zhang J, Wei S, Gao Y, Cao C, Wu Z. TPAFNet: transformer-driven pyramid attention fusion network for 3D medical image segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 16. link
Matey-Sanz M, González-Pérez A, Casteleyn S, Granell C. Implementing and Evaluating the Timed up and Go Test Automation Using Smartphones and Smartwatches. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 9. link
Wang G, Shanker S, Nag A, Lian Y, John D. ECG biometric authentication using self-supervised learning for IoT edge sensors. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 9. link
Cai T, Li X, Zhong C, Tang W, Guo J. DiffMAR: A Generalized Diffusion Model for Metal Artifact Reduction in CT Images. IEEE Journal of Biomedical and Health Informatics. 2024 Aug 7. link
Kobylińska K, Krzyziński M, Machowicz R, Adamek M, Biecek P. Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data. IEEE Journal of Biomedical and Health Informatics. 2024 Nov 6;28(11):6454-65. link
Salih AM, Galazzo IB, Raisi-Estabragh Z, Petersen SE, Menegaz G, Radeva P. Characterizing the contribution of dependent features in XAI methods. IEEE Journal of Biomedical and Health Informatics. 2024 May 2. link
Wang R, Veera SC, Asan O, Liao T. A Systematic Review on the Use of Consumer-Based ECG Wearables on Cardiac Health Monitoring. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 6. link
Matias P, Araújo R, Graça R, Henriques AR, Belo D, Valada M, Lotfi NN, Mateus EF, Radner H, Rodrigues AM, Studenic P. COTIDIANA Dataset–Smartphone-Collected Data on the Mobility, Finger Dexterity, and Mental Health of People With Rheumatic and Musculoskeletal Diseases. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 9. link
Qiu Y, Zhang H, Song C, Zhao X, Li H, Wang X. GKE-TUNet: Geometry-Knowledge Embedded TransUNet Model for Retinal Vessel Segmentation Considering Anatomical Topology. IEEE Journal of Biomedical and Health Informatics. 2024 Aug 13. link
Wang D, Han S, Xu Y, Wu Z, Zhou L, Morovati B, Yu H. LoMAE: simple streamlined low-level masked autoencoders for robust, generalized, and interpretable low-dose CT denoising. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 5. link
Huang J, Li X, Tan H, Cheng X. Generative adversarial network for trimodal medical image fusion using primitive relationship reasoning. IEEE Journal of Biomedical and Health Informatics. 2024 Aug 2. link
Avramidis K, Kunc D, Perz B, Adsul K, Feng T, Kazienko P, Saganowski S, Narayanan S. Scaling representation learning from ubiquitous ecg with state-space models. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 27. link
Park E, Lee Y. mDARTS: Searching ML-Based ECG Classifiers against Membership Inference Attacks. IEEE Journal of Biomedical and Health Informatics. 2024 Oct 16. link
Xu W, Lai C, Mo Z, Liu C, Li M, Zhao G, Xu K. Clinical-Inspired Framework for Automatic Kidney Stone Recognition and Analysis on Transverse CT Images. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 11. link
Li W, Liu T, Feng F, Yu S, Wang H, Sun Y. BTSSPro: Prompt-Guided Multimodal Co-Learning for Breast Cancer Tumor Segmentation and Survival Prediction. IEEE Journal of Biomedical and Health Informatics. 2024 May 31. link
Palmal S, Saha S, Arya N, Tripathy S. CAGCL: Predicting Short-and Long-Term Breast Cancer Survival with Cross-Modal Attention and Graph Contrastive Learning. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 5. link
Peng P, Fan W, Shen Y, Liu W, Yang X, Zhang Q, Wei X, Zhou D. Eye gaze guided cross-modal alignment network for radiology report generation. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 12. link
Huang H, Zhang C, Zhao L, Ding S, Wang H, Wu H. Self-supervised medical image denoising based on wista-net for human healthcare in metaverse. IEEE Journal of Biomedical and Health Informatics. 2023 May 22. link
Han B, Wang H, Qiao D, Xu J, Yan T. Application of zero-watermarking scheme based on swin transformer for securing the metaverse healthcare data. IEEE Journal of Biomedical and Health Informatics. 2023 Mar 15. link
Bai X, Chen G, Ma B, Li C, Zhang J, Xia Y. Exploratory Training for Universal Lesion Detection: Enhancing Lesion Mining Quality Through Temporal Verification. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 21. link
Qiu W, Feng Y, Li Y, Chang Y, Qian K, Hu B, Yamamoto Y, Schuller BW. Fed-MStacking: Heterogeneous Federated Learning With Stacking Misaligned Labels for Abnormal Heart Sound Detection. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 16. link
Lin WH, Zheng D, Li G, Chen F. Age-related changes in blood volume pulse wave at fingers and ears. IEEE Journal of Biomedical and Health Informatics. 2023 Jun 5. link
Li H, Ditzler G, Roveda J, Li A. Descod-ecg: Deep score-based diffusion model for ecg baseline wander and noise removal. IEEE Journal of Biomedical and Health Informatics. 2023 Jan 17. link
Pacheco AG, Cabello FA, Rodrigues PG, Miraldo DC, Fioravanti VB, Lima RG, Pinto PR, Fonoff AM, Penatti OA. Learning to estimate heart rate from accelerometer and user's demographics during physical exercises. IEEE Journal of Biomedical and Health Informatics. 2023 Mar 2. link
Jiang M, Bian F, Zhang J, Pu Z, Li H, Zhang Y, Chu Y, Fan Y, Jiang J. An Automatic Coronary Microvascular Dysfunction Classification Method Based on Hybrid ECG Features and Expert Features. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 26. link
Wu YC, Lin CH, Chiu LW, Wu BF, Chung ML, Tang SC, Sun Y. Contact-Free Atrial Fibrillation Screening with Attention Network. IEEE Journal of Biomedical and Health Informatics. 2024 Feb 27. link
Song Z, Qiu D, Zhao X, Liu R, Hui Y, Jiang H. Parallel alternating iterative optimization for cardiac magnetic resonance image blind super-resolution. IEEE Journal of Biomedical and Health Informatics. 2024 Jan 24;28(9):5136-46. link
Aublin PG, Felblinger J, Oster J. A Generalisable Heartbeat Classifier Leveraging Self-Supervised Learning for ECG Analysis During Magnetic Resonance Imaging. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 10. link
Ben-Moshe N, Tsutsui K, Biton S, Zvuloni E, Sörnmo L, Behar JA. RawECGNet: Deep learning generalization for atrial fibrillation detection from the raw ECG. IEEE Journal of Biomedical and Health Informatics. 2024 May 24. link
Li Y, Tan R, Lin T, Liu Q, Wang CD, Chen M. ER-GET: Emotion Recognition Based on Global ECG Trajectory. IEEE Journal of Biomedical and Health Informatics. 2024 May 30. link
Kim S, Lim J, Jang J. SeqAFNet: A Beat-Wise Sequential Neural Network for Atrial Fibrillation Classification in Adhesive Patch-Type Electrocardiographs. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 7. link
Huang Z, Li W, Wu Y, Yang L, Dong Y, Yang Y, Zheng H, Liang D, Wang M, Hu Z. Accurate Whole-Brain Image Enhancement for Low-Dose Integrated PET/MR Imaging Through Spatial Brain Transformation. IEEE Journal of Biomedical and Health Informatics. 2024 May 30. link
Mondol RK, Millar EK, Sowmya A, Meijering E. BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 24. link
Tsiknakis N, Manikis G, Tzoras E, Salgkamis D, Vidal JM, Wang K, Zaridis D, Sifakis E, Zerdes I, Bergh J, Hartman J. Unveiling the power of model-agnostic multiscale analysis for enhancing artificial intelligence models in breast cancer histopathology images. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 12. link
Zhang Y, Chung AC. Retinal Vessel Segmentation by A Transformer-U-Net Hybrid Model with Dual-Path Decoder. IEEE Journal of Biomedical and Health Informatics. 2024 Apr 26. link
Xu L, Tang Q, Zheng B, Lv J, Li W, Zeng X. CGFTrans: cross-modal global feature fusion transformer for medical report generation. IEEE Journal of Biomedical and Health Informatics. 2024 Jun 14. link
Zou X, He X, Zheng X, Zhang W, Chen J, Tang C. DAI-Net: Dual adaptive interaction network for coordinated medication recommendation. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 30. link
Santelices IB, LandryMember C, AramiMember A, Peterson SD. Employing deep reinforcement learning to maximize lower limb blood flow using intermittent pneumatic compression. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 5. link
Park S, Lee IJ, Kim JW, Ye JC. MS-DINO: Masked self-supervised distributed learning using vision transformer. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 5. link
Yan L, Guan Y, Wang H, Lin Y, Yang Y, Wang B, Jiang J. Eirad: An evidence-based dialogue system with highly interpretable reasoning path for automatic diagnosis. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 11. link
Pang C, Lu X, Liu X, Zhang R, Lyu L. IIAM: Intra and inter attention with mutual consistency learning network for medical image segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 10. link
Gu Y, Wu Q, Tang H, Mai X, Shu H, Li B, Chen Y. Lesam: Adapt segment anything model for medical lesion segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 May 29. link
Han T, Ai D, Fan J, Song H, Xiao D, Wang Y, Yang J. Cross-Anatomy Transfer Learning via Shape-Aware Adaptive Fine-Tuning for 3D Vessel Segmentation. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 2. link
Lu Y, Tan G, Pu B, Wang H, Liang B, Li K, Rajapakse JC. SKGC: A General Semantic-level Knowledge Guided Classification Framework for Fetal Congenital Heart Disease. IEEE Journal of Biomedical and Health Informatics. 2024 Jul 10. link
Xia T, Dang T, Han J, Qendro L, Mascolo C. Uncertainty-aware health diagnostics via class-balanced evidential deep learning. IEEE Journal of Biomedical and Health Informatics. 2024 Feb 6;28(11):6417-28. link
Yue G, Wei P, Zhou T, Song Y, Zhao C, Wang T, Lei B. Specificity-aware federated learning with dynamic feature fusion network for imbalanced medical image classification. IEEE Journal of Biomedical and Health Informatics. 2023 Sep 26. link
Sajid M, Hassan A, Khan DA, Khan SA, Bakhshi AD, Akram MU, Babar M, Hussain F, Abdul W. AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease using Novel Non-invasive Biomarkers. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 3. link
Wu F, Langer P, Shim J, Fleisch E, Barata F. Comparative efficacy of commercial wearables for circadian rhythm home monitoring from activity, heart rate, and core body temperature. IEEE Journal of Biomedical and Health Informatics. 2024 Sep 30. link
Iqbal S, Qureshi AN, Alhussein M, Aurangzeb K, Anwar MS. AD-CAM: Enhancing interpretability of convolutional neural networks with a lightweight framework-from black box to glass box. IEEE Journal of Biomedical and Health Informatics. 2023 Nov 1;28(1):514-25. link
Blinov P, Kokh V. Medical Profile Model: Scientific and Practical Applications in Healthcare. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 2;28(1):450-8. link
Miao D, Li J, Dou M, Fu L, Yao Y, Wang X, Wen F, Shen Y. A swintransformer-based segmentation framework with self-supervised strategy for post-operative prostate cancer radiotherapy. IEEE Journal of Biomedical and Health Informatics. 2023 Nov 1;28(1):403-14. link
Zhang M, Gu Y. Towards connectivity-aware pulmonary airway segmentation. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 12;28(1):321-32. link
Lyu F, Ye M, Yip TC, Wong GL, Yuen PC. Local style transfer via latent space manipulation for cross-disease lesion segmentation. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 26;28(1):273-84. link
Zhao X, Qi Z, Wang S, Wang Q, Wu X, Mao Y, Zhang L. Rcps: Rectified contrastive pseudo supervision for semi-supervised medical image segmentation. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 6;28(1):251-61. link
Zhang H, Liu W, Chang S, Wang H, He J, Huang Q. ST-ReGE: A novel spatial-temporal residual graph convolutional network for CVD. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 23;28(1):216-27. link
Fan Y, Gong H. An improved COVID-19 classification model on chest radiography by dual-ended multiple attention learning. IEEE Journal of Biomedical and Health Informatics. 2023 Oct 13;28(1):145-56. link
Lin X, Wang M, Li F, Xu Z, Chen J, Chen X, Yuan C, Wu S, Luo Y, Shen J, Feng ST. Improving tumor classification by reusing self-predicted segmentation of medical images as guiding knowledge. IEEE Journal of Biomedical and Health Informatics. 2023 Jul 6;28(1):122-33. link
Liu L, Wang Y, Zhang P, Qiao H, Sun T, Zhang H, Xu X, Shang H. Collaborative transfer network for multi-classification of breast cancer histopathological images. IEEE Journal of Biomedical and Health Informatics. 2023 Jun 9;28(1):110-21. link
Li W, Lam S, Wang Y, Liu C, Li T, Kleesiek J, Cheung AL, Sun Y, Lee FK, Au KH, Lee VH. Model generalizability investigation for GFCE-MRI synthesis in NPC radiotherapy using multi-institutional patient-based data normalization. IEEE journal of biomedical and health informatics. 2023 Aug 25;28(1):100-9. link
Zhao S, Li W, Liu Z, Pang T, Yang Y, Qiang N, Zhao J, Li B, Lei B, Han J. End-to-end prediction of EGFR mutation status with denseformer. IEEE Journal of Biomedical and Health Informatics. 2023 Aug 21;28(1):54-65. link
Song F, Tian J, Zhang P, Ma C, Sun Y, Feng Y, Zhang T, Lei Y, He Y, Cai Z, Cheng Y. A Novel Feature Engineering Method based on latent representation learning for Radiomics: application in NSCLC Subtype classification. IEEE Journal of Biomedical and Health Informatics. 2023 Jun 27;28(1):31-41. link
Zhao Z, Li W, Liu P, Zhang A, Sun J, Xu LX. Survival analysis for multimode ablation using self-adapted deep learning network based on multisource features. IEEE Journal of Biomedical and Health Informatics. 2023 Mar 31;28(1):19-30. link
Yan R, Lv Z, Yang Z, Lin S, Zheng C, Zhang F. Sparse and hierarchical Transformer for survival analysis on whole slide images. IEEE Journal of Biomedical and Health Informatics. 2023 Aug 22;28(1):7-18. link
Wang C, Kumar TS, De Raedt W, Camps G, Hallez H, Vanrumste B. Eat-Radar: Continuous fine-grained intake gesture detection using FMCW radar and 3D temporal convolutional network with attention. IEEE Journal of Biomedical and Health Informatics. 2023 Dec 5;28(2):1000-11. link
Jiang W, Chen K, Liang Z, Luo T, Yue G, Zhao Z, Song W, Zhao L, Wen J. HT-RCM: Hashimoto's Thyroiditis Ultrasound Image Classification Model Based on Res-FCT and Res-CAM. IEEE Journal of Biomedical and Health Informatics. 2023 Nov 10;28(2):941-51. link
Mahbub T, Obeid A, Javed S, Dias J, Hassan T, Werghi N. Center-Focused Affinity Loss for Class Imbalance Histology Image Classification. IEEE Journal of Biomedical and Health Informatics. 2023 Nov 24;28(2):952-63. link
Kobylińska K, Krzyziński M, Machowicz R, Adamek M, Biecek P. Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data. IEEE Journal of Biomedical and Health Informatics. 2024 Nov 6;28(11):6454-65. link
Yang Y, Xiang T, Lv X, Li L, Lui LM, Zeng T. Double Transformer Super-Resolution for Breast Cancer ADC Images. IEEE Journal of Biomedical and Health Informatics. 2023 Dec 11;28(2):917-28. link
Xinsen L, Yang K, Bingzhi C, Xiuhong C, Xinling L, Xinyao X, Jinlin C, Ming T, Pengtao L, Zheng X, Linying C. Vague-Segment Technique: Automatic Computation of Tumor Stroma Ratio for Breast Cancer on Whole Slides. IEEE Journal of Biomedical and Health Informatics. 2023 Dec 11;28(2):905-16. link
Zhang Y, Wang Y, Xu L, Yao Y, Qian W, Qi L. ST-GAN: A Swin Transformer-Based Generative Adversarial Network for Unsupervised Domain Adaptation of Cross-Modality Cardiac Segmentation. IEEE Journal of Biomedical and Health Informatics. 2023 Nov 29;28(2):893-904. link
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Aung N, Bartoli A, Rauseo E, Cortaredona S, Sanghvi MM, Fournel J, Ghattas B, Khanji MY, Petersen SE, Jacquier A. Left ventricular trabeculations at cardiac MRI: reference ranges and association with cardiovascular risk factors in UK Biobank. Radiology. 2024 Apr 2;311(1):e232455. link
Cozzi A, Pinker K, Hidber A, Zhang T, Bonomo L, Lo Gullo R, Christianson B, Curti M, Rizzo S, Del Grande F, Mann RM. BI-RADS category assignments by GPT-3.5, GPT-4, and Google Bard: a multilanguage study. Radiology. 2024 Apr 30;311(1):e232133. link
McCollough CH, Rajiah P, Bois JP, Winfree TN, Carter RE, Rajendran K, Williamson EE, Thorne JE, Leng S. Comparison of photon-counting detector and energy-integrating detector CT for visual estimation of coronary percent luminal stenosis. Radiology. 2023 Dec 5;309(3):e230853. link
Bernhard B, Leib Z, Dobner S, Demirel C, Caobelli F, Rominger A, Schütze J, Grogg H, Alwan L, Spano G, Boscolo Berto M. Routine 4D cardiac CT to identify concomitant transthyretin amyloid cardiomyopathy in older adults with severe aortic stenosis. Radiology. 2023 Dec 12;309(3):e230425. link
Bennani S, Regnard NE, Ventre J, Lassalle L, Nguyen T, Ducarouge A, Dargent L, Guillo E, Gouhier E, Zaimi SH, Canniff E. Using AI to improve radiologist performance in detection of abnormalities on chest radiographs. Radiology. 2023 Dec 12;309(3):e230860. link
Lyu J, Fu Y, Yang M, Xiong Y, Duan Q, Duan C, Wang X, Xing X, Zhang D, Lin J, Luo C. Generative adversarial network–based noncontrast CT angiography for aorta and carotid arteries. Radiology. 2023 Nov 14;309(2):e230681. link
Bachina P, Garin SP, Kulkarni P, Kanhere A, Sulam J, Parekh VS, Yi PH. Coarse race and ethnicity labels mask granular underdiagnosis disparities in deep learning models for chest radiograph diagnosis. Radiology. 2023 Nov 7;309(2):e231693. link
Arponen O, Ikonen JN, Kajantie E, Eriksson JG, Haapanen MJ. Frailty in late midlife to old age and its relationship to medical imaging use and imaging-related costs: a longitudinal study. Radiology. 2023 Nov 21;309(2):e230283. link
Henschke CI, Yip R, Shaham D, Markowitz S, Cervera Deval J, Zulueta JJ, Seijo LM, Aylesworth C, Klingler K, Andaz S, Chin C. A 20-year follow-up of the international early lung cancer action program (I-ELCAP). Radiology. 2023 Nov 7;309(2):e231988. link
Hickman SE, Payne NR, Black RT, Huang Y, Priest AN, Hudson S, Kasmai B, Juette A, Nanaa M, Aniq MI, Sienko A. Mammography breast cancer screening triage using deep learning: a UK retrospective study. Radiology. 2023 Nov 21;309(2):e231173. link
Zhou Z, Gao Y, Zhang W, Zhang N, Wang H, Wang R, Gao Z, Huang X, Zhou S, Dai X, Yang G. Deep learning–based prediction of percutaneous recanalization in chronic total occlusion using coronary CT angiography. Radiology. 2023 Nov 14;309(2):e231149. link
Guo B, Xing W, Hu C, Zha Y, Yin X, He Y, Hu S, Shi Y, Lv F, Wang R, Li X. Clinical effectiveness of automated coronary CT-derived fractional flow reserve: a Chinese randomized controlled trial. Radiology. 2024 Oct 15;313(1):e233354. link
Bhayana R, Fawzy A, Deng Y, Bleakney RR, Krishna S. Retrieval-augmented generation for large language models in radiology: another leap forward in board examination performance. Radiology. 2024 Oct 8;313(1):e241489. link
Sun SH, Huynh K, Cortes G, Hill R, Tran J, Yeh L, Ngo AL, Houshyar R, Yaghmai V, Tran M. Testing the ability and limitations of ChatGPT to generate differential diagnoses from transcribed radiologic findings. Radiology. 2024 Oct 15;313(1):e232346. link
Yun JK, Kim JY, Ahn Y, Kim MY, Lee GD, Choi S, Kim YH, Kim DK, Park SI, Kim HR. Predicting Recurrence after Sublobar Resection in Patients with Lung Adenocarcinoma Using Preoperative Chest CT Scans. Radiology. 2024 Oct 29;313(1):e233244. link
Hata A, Aoyagi K, Hino T, Kawagishi M, Wada N, Song J, Wang X, Valtchinov VI, Nishino M, Muraguchi Y, Nakatsugawa M. Automated interstitial lung abnormality probability prediction at CT: A Stepwise machine learning approach in the Boston lung Cancer study. Radiology. 2024 Sep 3;312(3):e233435. link
Mantz L, Mercaldo ND, Simon J, Kaess P, Yang K, Dietrich AS, Tonnesen PE, Troschel AS, Marquardt JP, Sehi DA, Javidan C. Preoperative Chest CT Myosteatosis Indicates Worse Postoperative Survival in Stage 0–IIB Non–Small Cell Lung Cancer. Radiology. 2025 Feb 11;314(2):e240282. link
Rodriguez-Takeuchi S, Tullis E, Babaei Jandaghi A, Yan AT, Colak E, Hall DA, Wong KC, Jiménez-Juan L, McIntyre K, Sykes J, Deva DP. Association between Cystic Fibrosis and Pericardial Calcification Detected at Chest CT in Adults. Radiology. 2025 Feb 25;314(2):e241793. link
Weir-McCall JR, Fitton CA, Gandy SJ, Lambert M, Littleford R, Houston JG, Belch JJ. Sex-specific associations between left ventricular remodeling at MRI and long-term cardiovascular risk. Radiology. 2024 Nov 5;313(2):e232997. link
Prinster D, Mahmood A, Saria S, Jeudy J, Lin CT, Yi PH, Huang CM. Care to explain? AI explanation types differentially impact chest radiograph diagnostic performance and physician trust in AI. Radiology. 2024 Nov 19;313(2):e233261. link
Dai N, Tang X, Hu Y, Lu H, Chen Z, Duan S, Guo W, Edavi PP, Yu Y, Huang D, Qian J. SARS-CoV-2 infection association with atherosclerotic plaque progression at coronary CT angiography and adverse cardiovascular events. Radiology. 2025 Feb 4;314(2):e240876. link
Langenbach IL, Hadzic I, Zeleznik R, Langenbach MC, Maintz D, Mayrhofer T, Lu MT, Aerts HJ, Foldyna B. Association of epicardial adipose tissue changes on serial chest CT scans with mortality: insights from the national lung screening trial. Radiology. 2025 Feb 18;314(2):e240473. link
Bhayana R, Alwahbi O, Ladak AM, Deng Y, Basso Dias A, Elbanna K, Abreu Gomez J, Jajodia A, Jhaveri K, Johnson S, Kajal D. Leveraging large language models to generate clinical histories for oncologic imaging requisitions. Radiology. 2025 Feb 4;314(2):e242134. link
Akinci D’Antonoli T, Berger LK, Indrakanti AK, Vishwanathan N, Weiss J, Jung M, Berkarda Z, Rau A, Reisert M, Küstner T, Walter A. Totalsegmentator mri: Robust sequence-independent segmentation of multiple anatomic structures in mri. Radiology. 2025 Feb 18;314(2):e241613. link
Steinhelfer L, Jungmann F, Nickel M, Kaissis G, Hofer ML, Tauber R, Schmaderer C, Rauscher I, Haller B, Makowski MR, Eiber M. Automated CT Measurement of Total Kidney Volume for Predicting Renal Function Decline after 177Lu Prostate-specific Membrane Antigen–I&T Radioligand Therapy. Radiology. 2025 Feb 25;314(2):e240427. link
Marinescu DC, Hague CJ, Muller NL, Murphy D, Churg A, Wright JL, Al-Arnawoot A, Bilawich AM, Bourgouin P, Cox G, Durand C. CT Honeycombing and Traction Bronchiectasis Extent Independently Predict Survival across Fibrotic Interstitial Lung Disease Subtypes. Radiology. 2025 Feb 4;314(2):e241001. link
Baffour FI, Huber NR, Ferrero A, Rajendran K, Glazebrook KN, Larson NB, Kumar S, Cook JM, Leng S, Shanblatt ER, McCollough CH. Photon-counting detector CT with deep learning noise reduction to detect multiple myeloma. Radiology. 2023 Jan;306(1):229-36. link
Chen PT, Wu T, Wang P, Chang D, Liu KL, Wu MS, Roth HR, Lee PC, Liao WC, Wang W. Pancreatic cancer detection on CT scans with deep learning: a nationwide population-based study. Radiology. 2023 Jan;306(1):172-82. link
Bian Y, Zheng Z, Fang X, Jiang H, Zhu M, Yu J, Zhao H, Zhang L, Yao J, Lu L, Lu J. Artificial intelligence to predict lymph node metastasis at CT in pancreatic ductal adenocarcinoma. Radiology. 2023 Jan;306(1):160-9. link
Park HJ, Shin K, You MW, Kyung SG, Kim SY, Park SH, Byun JH, Kim N, Kim HJ. Deep learning–based detection of solid and cystic pancreatic neoplasms at contrast-enhanced CT. Radiology. 2023 Jan;306(1):140-9. link
Kazemzadeh S, Yu J, Jamshy S, Pilgrim R, Nabulsi Z, Chen C, Beladia N, Lau C, McKinney SM, Hughes T, Kiraly AP. Deep learning detection of active pulmonary tuberculosis at chest radiography matched the clinical performance of radiologists. Radiology. 2023 Jan;306(1):124-37. link
Figliozzi S, Georgiopoulos G, Lopes PM, Bauer KB, Moura-Ferreira S, Tondi L, Mushtaq S, Censi S, Pavon AG, Bassi I, Servato ML. Myocardial fibrosis at cardiac MRI helps predict adverse clinical outcome in patients with mitral valve prolapse. Radiology. 2023 Jan;306(1):112-21. link
Kolossváry M, Raghu VK, Nagurney JT, Hoffmann U, Lu MT. Deep learning analysis of chest radiographs to triage patients with acute chest pain syndrome. Radiology. 2023 Jan 17;306(2):e221926. link
Lee JE, Chae KJ, Suh YJ, Jeong WG, Lee T, Kim YH, Jin GY, Jeong YJ. Prevalence and long-term outcomes of CT interstitial lung abnormalities in a health screening cohort. Radiology. 2022 Oct 11;306(2):e221172. link
Beheshtian E, Putman K, Santomartino SM, Parekh VS, Yi PH. Generalizability and bias in a deep learning pediatric bone age prediction model using hand radiographs. Radiology. 2022 Sep 27;306(2):e220505. link
Robinson-Weiss C, Patel J, Bizzo BC, Glazer DI, Bridge CP, Andriole KP, Dabiri B, Chin JK, Dreyer K, Kalpathy-Cramer J, Mayo-Smith WW. Machine learning for adrenal gland segmentation and classification of normal and adrenal masses at CT. Radiology. 2022 Sep 20;306(2):e220101. link
Lee MH, Zea R, Garrett JW, Graffy PM, Summers RM, Pickhardt PJ. Abdominal CT body composition thresholds using automated AI tools for predicting 10-year adverse outcomes. Radiology. 2022 Sep 27;306(2):e220574. link
Wang L, Wang Y, Wang J, Xiao M, Xi XY, Chen BX, Su Y, Zhang Y, Xie B, Dong Z, Zhao S. Myocardial activity at 18F-FAPI PET/CT and risk for sudden cardiac death in hypertrophic cardiomyopathy. Radiology. 2022 Oct 11;306(2):e221052. link
Mauger CA, Gilbert K, Suinesiaputra A, Bluemke DA, Wu CO, Lima JA, Young AA, Ambale-Venkatesh B. Multi-ethnic study of atherosclerosis: relationship between left ventricular shape at cardiac MRI and 10-year outcomes. Radiology. 2022 Sep 20;306(2):e220122. link
Dodd JD, Leipsic JA. Evolving developments in cardiac CT. Radiology. 2023 Mar 28;307(3):e222827. link
Rajiah PS, François CJ, Leiner T. Cardiac MRI: state of the art. Radiology. 2023 Apr 11;307(3):e223008. link
Müller-Franzes G, Huck L, Tayebi Arasteh S, Khader F, Han T, Schulz V, Dethlefsen E, Kather JN, Nebelung S, Nolte T, Kuhl C. Using machine learning to reduce the need for contrast agents in breast MRI through synthetic images. Radiology. 2023 Mar 21;307(3):e222211. link
Li Y, Xu Y, Li W, Guo J, Wan K, Wang J, Xu Z, Han Y, Sun J, Chen Y. Cardiac MRI to predict sudden cardiac death risk in dilated cardiomyopathy. Radiology. 2023 Mar 14;307(3):e222552. link
Ghanbari F, Joyce T, Lorenzoni V, Guaricci AI, Pavon AG, Fusini L, Andreini D, Rabbat MG, Aquaro GD, Abete R, Bogaert J. AI cardiac MRI scar analysis aids prediction of major arrhythmic events in the multicenter DERIVATE registry. Radiology. 2023 Mar 21;307(3):e222239. link
Plesner LL, Müller FC, Nybing JD, Laustrup LC, Rasmussen F, Nielsen OW, Boesen M, Andersen MB. Autonomous chest radiograph reporting using AI: estimation of clinical impact. Radiology. 2023 Mar 7;307(3):e222268. link
Park S, Lee SM, Choe J, Choi S, Do KH, Seo JB. Recurrence patterns and patient outcomes in resected lung adenocarcinoma differ according to ground-glass opacity at CT. Radiology. 2023 Mar 21;307(3):e222422. link
Chen Q, Pan T, Wang YN, Schoepf UJ, Bidwell SL, Qiao H, Feng Y, Xu C, Xu H, Xie G, Gao X. A coronary CT angiography radiomics model to identify vulnerable plaque and predict cardiovascular events. Radiology. 2023 Feb 14;307(2):e221693. link
Aitken M, Davidson M, Chan MV, Urzua Fresno C, Vasquez LI, Huo YR, McAllister BJ, Broncano J, Thavendiranathan P, McInnes MD, Iwanochko MR. Prognostic value of cardiac MRI and FDG PET in cardiac sarcoidosis: a systematic review and meta-analysis. Radiology. 2023 Feb 21;307(2):e222483. link
Wang C, Huang Y, Liu C, Liu F, Hu X, Kuang X, An W, Liu C, Liu Y, Liu S, He R. Diagnosis of clinically significant portal hypertension using CT-and MRI-based vascular model. Radiology. 2023 Jan 31;307(2):e221648. link
Johnson PM, Lin DJ, Zbontar J, Zitnick CL, Sriram A, Muckley M, Babb JS, Kline M, Ciavarra G, Alaia E, Samim M. Deep learning reconstruction enables prospectively accelerated clinical knee MRI. Radiology. 2023 Jan 17;307(2):e220425. link
Jones BC, Lee H, Cheng CC, Al Mukaddam M, Song HK, Snyder PJ, Kamona N, Rajapakse CS, Wehrli FW. MRI quantification of cortical bone porosity, mineralization, and morphologic structure in postmenopausal osteoporosis. Radiology. 2023 Jan 24;307(2):e221810. link
Nam JG, Hwang EJ, Kim J, Park N, Lee EH, Kim HJ, Nam M, Lee JH, Park CM, Goo JM. AI improves nodule detection on chest radiographs in a health screening population: a randomized controlled trial. Radiology. 2023 Feb 7;307(2):e221894. link
Park H, Yun J, Lee SM, Hwang HJ, Seo JB, Jung YJ, Hwang J, Lee SH, Lee SW, Kim N. Deep learning–based approach to predict pulmonary function at chest CT. Radiology. 2023 Feb 14;307(2):e221488. link
Han X, Chen L, Fan Y, Alwalid O, Jia X, Zheng Y, Liu J, Li Y, Cao Y, Gu J, Liu J. Longitudinal assessment of chest CT findings and pulmonary function after COVID-19 infection. Radiology. 2023 Feb 14;307(2):e222888. link
Khader F, Han T, Müller-Franzes G, Huck L, Schad P, Keil S, Barzakova E, Schulze-Hagen M, Pedersoli F, Schulz V, Zimmermann M. Artificial intelligence for clinical interpretation of bedside chest radiographs. Radiology. 2022 Dec 6;307(1):e220510. link
Gidwani M, Chang K, Patel JB, Hoebel KV, Ahmed SR, Singh P, Fuller CD, Kalpathy-Cramer J. Inconsistent partitioning and unproductive feature associations yield idealized radiomic models. Radiology. 2022 Dec 20;307(1):e220715. link
Kim H, Jin KN, Yoo SJ, Lee CH, Lee SM, Hong H, Witanto JN, Yoon SH. Deep learning for estimating lung capacity on chest radiographs predicts survival in idiopathic pulmonary fibrosis. Radiology. 2022 Oct 25;306(3):e220292. link
Li S, Wang Y, Yang W, Zhou D, Zhuang B, Xu J, He J, Yin G, Fan X, Wu W, Sharma P. Cardiac MRI risk stratification for dilated cardiomyopathy with left ventricular ejection fraction of 35% or higher. Radiology. 2022 Nov 1;306(3):e213059. link
Li M, Ling R, Yu L, Yang W, Chen Z, Wu D, Zhang J. Deep learning segmentation and reconstruction for CT of chronic total coronary occlusion. Radiology. 2022 Oct 25;306(3):e221393. link
Kidoh M, Oda S, Takashio S, Hirakawa K, Kawano Y, Shiraishi S, Hayashi H, Nakaura T, Nagayama Y, Funama Y, Ueda M. CT extracellular volume fraction versus myocardium-to-lumen signal ratio for cardiac amyloidosis. Radiology. 2022 Oct 18;306(3):e220542. link
Barros V, Tlusty T, Barkan E, Hexter E, Gruen D, Guindy M, Rosen-Zvi M. Virtual biopsy by using artificial intelligence–based multimodal modeling of binational mammography data. Radiology. 2022 Oct 25;306(3):e220027. link
Acciavatti RJ, Lee SH, Reig B, Moy L, Conant EF, Kontos D, Moon WK. Beyond breast density: risk measures for breast cancer in multiple imaging modalities. Radiology. 2023 Feb 7;306(3):e222575. link
Koetzier LR, Mastrodicasa D, Szczykutowicz TP, van der Werf NR, Wang AS, Sandfort V, van der Molen AJ, Fleischmann D, Willemink MJ. Deep learning image reconstruction for CT: technical principles and clinical prospects. Radiology. 2023 Jan 31;306(3):e221257. link
Calle-Toro J, Viteri B, Ballester L, García-Perdomo HA, White A, Pradhan M, Otero HJ. Risk of acute kidney injury following contrast-enhanced CT in a cohort of 10 407 children and adolescents. Radiology. 2022 Dec 6;307(1):e210816. link
Hanneman K, Houbois C, Kei T, Gustafson D, Thampinathan B, Sooriyakanthan M, Fish JE, Howe KL, Cheung AM, Wintersperger BJ, Gold WL. Multimodality cardiac imaging, cardiac symptoms, and clinical outcomes in patients who recovered from mild COVID-19. Radiology. 2023 Jul 11;308(1):e230767. link
Longuefosse A, Raoult J, Benlala I, Denis de Senneville B, Benkert T, Macey J, Bui S, Berger P, Ferretti G, Gaubert JY, Liberge R. Generating high-resolution synthetic CT from lung MRI with ultrashort echo times: initial evaluation in cystic fibrosis. Radiology. 2023 Jul 5;308(1):e230052. link
Xu K, Khan MS, Li TZ, Gao R, Terry JG, Huo Y, Lasko TA, Carr JJ, Maldonado F, Landman BA, Sandler KL. AI body composition in lung cancer screening: added value beyond lung cancer detection. Radiology. 2023 Jul 25;308(1):e222937. link
Arasu VA, Habel LA, Achacoso NS, Buist DS, Cord JB, Esserman LJ, Hylton NM, Glymour MM, Kornak J, Kushi LH, Lewis DA. Comparison of mammography AI algorithms with a clinical risk model for 5-year breast cancer risk prediction: an observational study. Radiology. 2023 Jun 6;307(5):e222733. link
Damiani C, Kalliatakis G, Sreenivas M, Al-Attar M, Rose J, Pudney C, Lane EF, Cuzick J, Montana G, Brentnall AR. Evaluation of an AI model to assess future breast cancer risk. Radiology. 2023 Jun 13;307(5):e222679. link
Beuque MP, Lobbes MB, van Wijk Y, Widaatalla Y, Primakov S, Majer M, Balleyguier C, Woodruff HC, Lambin P. Combining deep learning and handcrafted radiomics for classification of suspicious lesions on contrast-enhanced mammograms. Radiology. 2023 Jun 20;307(5):e221843. link
Yoon S, Nakamori S, Amyar A, Assana S, Cirillo J, Morales MA, Chow K, Bi X, Pierce P, Goddu B, Rodriguez J. Accelerated cardiac MRI cine with use of resolution enhancement generative adversarial inline neural network. Radiology. 2023 May 30;307(5):e222878. link
Zhou J, Li C, Zhang H, Liu C, Yang J, Zhao J, Hou Y, Tan Y, Wang H, Li Y, Xie C. Association between coronary artery disease reporting and data system–recommended post–coronary CT angiography management and clinical outcomes in patients with stable chest pain from a Chinese registry. Radiology. 2023 Jun 13;307(5):e222965. link
Chae KJ, Lim S, Seo JB, Hwang HJ, Choi H, Lynch D, Jin GY. Interstitial lung abnormalities at CT in the Korean National Lung Cancer Screening Program: prevalence and deep learning–based texture analysis. Radiology. 2023 Apr 25;307(4):e222828. link
Baraghoshi D, Strand M, Humphries SM, San José Estépar R, Vegas Sanchez-Ferrero G, Charbonnier JP, Latisenko R, Silverman EK, Crapo JD, Lynch DA. Quantitative CT evaluation of emphysema progression over 10 years in the COPDGene study. Radiology. 2023 Apr 11;307(4):e222786. link
Lee JH, Hong H, Nam G, Hwang EJ, Park CM. Effect of human-AI interaction on detection of malignant lung nodules on chest radiographs. Radiology. 2023 Jun 27;307(5):e222976. link
Amudala Puchakayala PR, Sthanam VL, Nakhmani A, Chaudhary MF, Kizhakke Puliyakote A, Reinhardt JM, Zhang C, Bhatt SP, Bodduluri S. Radiomics for improved detection of chronic obstructive pulmonary disease in low-dose and standard-dose chest CT scans. Radiology. 2023 Jun 20;307(5):e222998. link
Lee CC, Chan YL, Wong YC, Ng CJ, Chang CH, Hung CC, Su TH. Contrast-enhanced CT and acute kidney injury: risk stratification by diabetic status and kidney function. Radiology. 2023 Jun 6;307(5):e222321. link
Yoon JH, Strand F, Baltzer PA, Conant EF, Gilbert FJ, Lehman CD, Morris EA, Mullen LA, Nishikawa RM, Sharma N, Vejborg I. Standalone AI for breast cancer detection at screening digital mammography and digital breast tomosynthesis: a systematic review and meta-analysis. Radiology. 2023 May 23;307(5):e222639. link
Prosper AE, Kammer MN, Maldonado F, Aberle DR, Hsu W. Expanding role of advanced image analysis in CT-detected indeterminate pulmonary nodules and early lung cancer characterization. Radiology. 2023 Oct 10;309(1):e222904. link
McCollough CH, Rajiah PS. Milestones in CT: past, present, and future. Radiology. 2023 Oct 17;309(1):e230803. link
Larsen M, Olstad CF, Koch HW, Martiniussen MA, Hoff SR, Lund-Hanssen H, Solli HS, Mikalsen KØ, Auensen S, Nygård J, Lång K. AI risk score on screening mammograms preceding breast cancer diagnosis. Radiology. 2023 Oct 17;309(1):e230989. link
Khader F, Müller-Franzes G, Wang T, Han T, Tayebi Arasteh S, Haarburger C, Stegmaier J, Bressem K, Kuhl C, Nebelung S, Kather JN. Multimodal deep learning for integrating chest radiographs and clinical parameters: a case for transformers. Radiology. 2023 Oct 3;309(1):e230806. link
Heo S, Lee SS, Choi SH, Kim DW, Park HJ, Kim SY, Lee SJ, Kim KM, Shin YM. CT rule-in and rule-out criteria for clinically significant portal hypertension in chronic liver disease. Radiology. 2023 Oct 31;309(1):e231208. link
Rothenberg SA, Savage CH, Abou Elkassem A, Singh S, Abozeed M, Hamki O, Junck K, Tridandapani S, Li M, Li Y, Smith AD. Prospective evaluation of AI triage of pulmonary emboli on CT pulmonary angiograms. Radiology. 2023 Oct 3;309(1):e230702. link
Yun J, Ahn Y, Cho K, Oh SY, Lee SM, Kim N, Seo JB. Deep learning for automated triaging of stable chest radiographs in a follow-up setting. Radiology. 2023 Oct 24;309(1):e230606. link
Chen Y, Taib AG, Darker IT, James JJ. Performance of a breast cancer detection AI algorithm using the personal performance in mammographic screening scheme. Radiology. 2023 Sep 5;308(3):e223299. link
Lamb LR, Mercaldo SF, Ghaderi K, Carney A, Lehman CD. Comparison of the diagnostic accuracy of mammogram-based deep learning and traditional breast cancer risk models in patients who underwent supplemental screening with MRI. Radiology. 2023 Sep 19;308(3):e223077. link
Watt GP, Thakran S, Sung JS, Jochelson MS, Lobbes MB, Weinstein SP, Bradbury AR, Buys SS, Morris EA, Apte A, Patel P. Association of breast cancer odds with background parenchymal enhancement quantified using a fully automated method at MRI: The IMAGINE study. Radiology. 2023 Sep 26;308(3):e230367. link
Iriart X, Blanc G, Bouteiller XP, Legghe B, Bouyer B, Sridi-Cheniti S, Bustin A, Vasile C, Thambo JB, Elbaz M, Cochet H. Clinical implications of CT-detected hypoattenuation thickening on left atrial appendage occlusion devices. Radiology. 2023 Sep 5;308(3):e230462. link
Madsen KT, Nørgaard BL, Øvrehus KA, Jensen JM, Parner E, Grove EL, Fairbairn TA, Nieman K, Patel MR, Rogers C, Mullen S. Prognostic value of coronary CT angiography–derived fractional flow reserve on 3-year outcomes in patients with stable angina. Radiology. 2023 Sep 12;308(3):e230524. link
Alves N, Bosma JS, Venkadesh KV, Jacobs C, Saghir Z, De Rooij M, Hermans J, Huisman H. Prediction variability to identify reduced AI performance in cancer diagnosis at MRI and CT. Radiology. 2023 Sep 19;308(3):e230275. link
Lind Plesner L, Müller FC, Brejnebøl MW, Laustrup LC, Rasmussen F, Nielsen OW, Boesen M, Brun Andersen M. Commercially available chest radiograph AI tools for detecting airspace disease, pneumothorax, and pleural effusion. Radiology. 2023 Sep 26;308(3):e231236. link
Gruenewald LD, Koch V, Martin SS, Yel I, Mahmoudi S, Bernatz S, Eichler K, Gruber-Rouh T, Pinto Dos Santos D, D’Angelo T, Wesarg S. Dual-energy CT-based opportunistic volumetric bone mineral density assessment of the distal radius. Radiology. 2023 Aug 8;308(2):e223150. link
Venkadesh KV, Aleef TA, Scholten ET, Saghir Z, Silva M, Sverzellati N, Pastorino U, van Ginneken B, Prokop M, Jacobs C. Prior CT improves deep learning for malignancy risk estimation of screening-detected pulmonary nodules. Radiology. 2023 Aug 1;308(2):e223308. link
Faghani S, Moassefi M, Rouzrokh P, Khosravi B, Baffour FI, Ringler MD, Erickson BJ. Quantifying uncertainty in deep learning of radiologic images. Radiology. 2023 Aug 1;308(2):e222217. link
Lauritzen AD, von Euler-Chelpin MC, Lynge E, Vejborg I, Nielsen M, Karssemeijer N, Lillholm M. Assessing breast cancer risk by combining AI for lesion detection and mammographic texture. Radiology. 2023 Aug 29;308(2):e230227. link
Lu ZF, Yin WH, Schoepf UJ, Abrol S, Ma JW, Yu XB, Zhao L, Su XM, Wang CS, An YQ, Xiao ZC. Residual risk in non–ST-segment elevation acute coronary syndrome: quantitative plaque analysis at coronary CT angiography. Radiology. 2023 Aug 22;308(2):e230124. link