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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Zhou Q, Zuley M, Guo Y, Yang L, Nair B, Vargo A, Ghannam S, Arefan D, Wu S. A machine and human reader study on AI diagnosis model safety under attacks of adversarial images. Nature communications. 2021 Dec 14;12(1):7281. link
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Lima EM, Ribeiro AH, Paixão GM, Ribeiro MH, Pinto-Filho MM, Gomes PR, Oliveira DM, Sabino EC, Duncan BB, Giatti L, Barreto SM. Deep neural network-estimated electrocardiographic age as a mortality predictor. Nature communications. 2021 Aug 25;12(1):5117. link
Goto S, Mahara K, Beussink-Nelson L, Ikura H, Katsumata Y, Endo J, Gaggin HK, Shah SJ, Itabashi Y, MacRae CA, Deo RC. Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms. Nature communications. 2021 May 11;12(1):2726. link
Zeleznik R, Foldyna B, Eslami P, Weiss J, Alexander I, Taron J, Parmar C, Alvi RM, Banerji D, Uno M, Kikuchi Y. Deep convolutional neural networks to predict cardiovascular risk from computed tomography. Nature communications. 2021 Jan 29;12(1):715. link
Wang S, Li C, Wang R, Liu Z, Wang M, Tan H, Wu Y, Liu X, Sun H, Yang R, Liu X. Annotation-efficient deep learning for automatic medical image segmentation. Nature communications. 2021 Oct 8;12(1):5915. link
Chao H, Shan H, Homayounieh F, Singh R, Khera RD, Guo H, Su T, Wang G, Kalra MK, Yan P. Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography. Nature Communications. 2021 May 20;12(1):2963. link
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Schulz MA, Yeo BT, Vogelstein JT, Mourao-Miranada J, Kather JN, Kording K, Richards B, Bzdok D. Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets. Nat Commun 11, 4238 [Internet]. 2020 link
Harmon SA, Sanford TH, Xu S, Turkbey EB, Roth H, Xu Z, Yang D, Myronenko A, Anderson V, Amalou A, Blain M. Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets. Nature communications. 2020 Aug 14;11(1):4080. link
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Varadarajan AV, Bavishi P, Ruamviboonsuk P, Chotcomwongse P, Venugopalan S, Narayanaswamy A, Cuadros J, Kanai K, Bresnick G, Tadarati M, Silpa-Archa S. Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning. Nature communications. 2020 Jan 8;11(1):130. link
Van de Ven GM, Siegelmann HT, Tolias AS. Brain-inspired replay for continual learning with artificial neural networks. Nature communications. 2020 Aug 13;11(1):4069. link
Cohen EA, Abraham AV, Ramakrishnan S, Ober RJ. Resolution limit of image analysis algorithms. Nature communications. 2019 Feb 15;10(1):793. link
Fries JA, Varma P, Chen VS, Xiao K, Tejeda H, Saha P, Dunnmon J, Chubb H, Maskatia S, Fiterau M, Delp S. Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences. Nature communications. 2019 Jul 15;10(1):3111. link
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Riaz IB, Naqvi SA, Ashraf N, Harris GJ, Kehl KL. Empirical evaluation of artificial intelligence distillation techniques for ascertaining cancer outcomes from electronic health records. npj Digital Medicine. 2025 Jun 10;8(1):347. link
Ong AY, Taribagil P, Sevgi M, Kale AU, Dow ER, Macdonald T, Kras A, Maniatopoulos G, Liu X, Keane PA, Denniston AK. A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America. npj Digital Medicine. 2025 May 29;8(1):323. link
Handley JL, Krevat SA, Fong A, Ratwani RM. Artificial intelligence related safety issues associated with FDA medical device reports. npj Digital Medicine. 2024 Dec 3;7(1):351. link
Motazedian P, Marbach JA, Prosperi-Porta G, Parlow S, Di Santo P, Abdel-Razek O, Jung R, Bradford WB, Tsang M, Hyon M, Pacifici S. Diagnostic accuracy of point-of-care ultrasound with artificial intelligence-assisted assessment of left ventricular ejection fraction. NPJ Digital Medicine. 2023 Oct 28;6(1):201. Link
Miao H, Liu S, Wang Z, Ke Y, Cheng L, Yu W, Yu D, Zhang K, Gao Y, Sun Z. Artificial intelligence-derived retinal age gap as a marker for reproductive aging in women. npj Digital Medicine. 2025 Jun 16;8(1):367. link
Mossavarali S, Vaezi A, Gholami Z, Molaei A, Yekaninejad MS, Asselbergs FW, Shafiee A. Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis. npj Digital Medicine. 2025 May 29;8(1):322. link
Choi DJ, Park JJ, Ali T, Lee S. Artificial intelligence for the diagnosis of heart failure. NPJ digital medicine. 2020 Apr 8;3(1):54. link
Wang S, Liu X, Yuan S, Bian Y, Wu H, Ye Q. Artificial intelligence based multispecialty mortality prediction models for septic shock in a multicenter retrospective study. NPJ Digital Medicine. 2025 Apr 28;8(1):1-0. link
Ferreira TJ, Salvador IC, Pessanha CR, da Silva RR, Pereira AD, Horst MA, Carvalho DP, Koury JC, Pierucci AP. Advances in the estimation of body fat percentage using an artificial intelligence 2D-photo method. npj Digital Medicine. 2025 Jan 18;8(1):43. link
Naghavi M, Reeves AP, Atlas K, Zhang C, Atlas T, Henschke CI, Yankelevitz DF, Budoff MJ, Li D, Roy SK, Nasir K. Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction. npj Digital Medicine. 2024 Nov 5;7(1):309. link
Fountzilas E, Pearce T, Baysal MA, Chakraborty A, Tsimberidou AM. Convergence of evolving artificial intelligence and machine learning techniques in precision oncology. NPJ Digital Medicine. 2025 Jan 31;8(1):75. link
Park H, Kwon OS, Shim J, Kim D, Park JW, Kim YG, Yu HT, Kim TH, Uhm JS, Choi JI, Joung B. Artificial intelligence-estimated electrocardiographic sex as a recurrence predictor after atrial fibrillation catheter ablation. European Heart Journal-Digital Health. 2025 Jul;6(4):624-34. link
Schmidt J, Schutte NM, Buttigieg S, Novillo-Ortiz D, Sutherland E, Anderson M, de Witte B, Peolsson M, Unim B, Pavlova M, Stern AD. Mapping the regulatory landscape for artificial intelligence in health within the European Union. npj Digital Medicine. 2024 Aug 27;7(1):229. link
Adapa K, Gupta A, Singh S, Kaur H, Trikha A, Sharma A, Rahul K. A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening. npj Digital Medicine. 2025 Jan 2;8(1):2. link
Lee E, Ito S, Miranda WR, Lopez-Jimenez F, Kane GC, Asirvatham SJ, Noseworthy PA, Friedman PA, Carter RE, Borlaug BA, Attia ZI. Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure. npj Digital Medicine. 2024 Jan 6;7(1):4. link
Somani S, Balla S, Peng AW, Dudum R, Jain S, Nasir K, Maron DJ, Hernandez-Boussard T, Rodriguez F. Contemporary attitudes and beliefs on coronary artery calcium from social media using artificial intelligence. NPJ digital medicine. 2024 Mar 30;7(1):83. link
Pastika L, Sau A, Patlatzoglou K, Sieliwonczyk E, Ribeiro AH, McGurk KA, Khan S, Mandic D, Scott WR, Ware JS, Peters NS. Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease. npj Digital Medicine. 2024 Jun 25;7(1):167. link
Kim CK, Choi JW, Jiao Z, Wang D, Wu J, Yi TY, Halsey KC, Eweje F, Tran TM, Liu C, Wang R. An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data. NPJ Digital Medicine. 2022 Jan 14;5(1):5. link
Lin C, Chau T, Lin CS, Shang HS, Fang WH, Lee DJ, Lee CC, Tsai SH, Wang CH, Lin SH. Point-of-care artificial intelligence-enabled ECG for dyskalemia: a retrospective cohort analysis for accuracy and outcome prediction. NPJ digital medicine. 2022 Jan 19;5(1):8. link
Wiegand TL, Jung LB, Gudera JA, Schuhmacher LS, Moehrle P, Rischewski JF, Mehrzad P, Jeong S, Nguyen LH, Poeschla M, Velezmoro LI. Demographic inaccuracies and biases in the depiction of patients by artificial intelligence text-to-image generators. NPJ Digital Medicine. 2025 Jul 19;8(1):459. link
Vega R, Dehghan M, Nagdev A, Buchanan B, Kapur J, Jaremko JL, Zonoobi D. Overcoming barriers in the use of artificial intelligence in point of care ultrasound. npj Digital Medicine. 2025 Apr 19;8(1):213. link
Wang J, Xue L, Jiang J, Liu F, Wu P, Lu J, Zhang H, Bao W, Xu Q, Ju Z, Chen L. Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson’s disease: a systematic review and meta-analysis. NPJ Digital Medicine. 2024 Jan 22;7(1):17. link
Young AT, Fernandez K, Pfau J, Reddy R, Cao NA, von Franque MY, Johal A, Wu BV, Wu RR, Chen JY, Fadadu RP. Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models. NPJ digital medicine. 2021 Jan 21;4(1):10. link
Benjamens S, Dhunnoo P, Meskó B. The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. NPJ digital medicine. 2020 Sep 11;3(1):118. link
O’Sullivan D, Anjewierden S, Greason G, Attia IZ, Lopez-Jimenez F, Friedman PA, Noseworthy P, Anderson J, Kashou A, Asirvatham SJ, Eidem BW. Pediatric sex estimation using AI-enabled ECG analysis: influence of pubertal development. NPJ Digital Medicine. 2024 Jul 2;7(1):176. link
Zeleznik R, Weiss J, Taron J, Guthier C, Bitterman DS, Hancox C, Kann BH, Kim DW, Punglia RS, Bredfeldt J, Foldyna B. Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer. NPJ digital medicine. 2021 Mar 5;4(1):43. link
Loni M, Poursalim F, Asadi M, Gharehbaghi A. A review on generative AI models for synthetic medical text, time series, and longitudinal data. npj Digital Medicine. 2025 May 15;8(1):281. link
Yin P, Wang J, Zhang C, Tang Y, Hu X, Shu H, Wang J, Liu B, Yu Y, Zhou Y, Li X. Prediction of functional outcomes in aneurysmal subarachnoid hemorrhage using pre-/postoperative noncontrast CT within 3 days of admission. npj Digital Medicine. 2025 Aug 24;8(1):542. link
Li R, Wang X, Berlowitz D, Mez J, Lin H, Yu H. CARE-AD: a multi-agent large language model framework for Alzheimer’s disease prediction using longitudinal clinical notes. npj Digital Medicine. 2025 Aug 24;8(1):541. link
Munjal P, Mahrooqi AA, Rajan R, Jeremijenko A, Ahmad I, Akhtar MI, Pimentel MA, Khan S. Population-scale cross-sectional observational study for AI-powered TB screening on one million CXRs. npj Digital Medicine. 2025 Jul 9;8(1):418. link
Zhu M, Lin H, Jiang J, Jinia AJ, Jee J, Pichotta K, Waters M, Rose D, Schultz N, Chalise S, Valleru L. Large language model trained on clinical oncology data predicts cancer progression. npj Digital Medicine. 2025 Jul 2;8(1):397. link
Yu P, Zhang H, Wang D, Zhang R, Deng M, Yang H, Wu L, Liu X, Oh AS, Abtin FG, Prosper AE. Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT. npj Digital Medicine. 2024 Nov 23;7(1):335. link
Gaber F, Shaik M, Allega F, Bilecz AJ, Busch F, Goon K, Franke V, Akalin A. Evaluating large language model workflows in clinical decision support for triage and referral and diagnosis. npj Digital Medicine. 2025 May 9;8(1):263. link
van Vliet M, Aalberts JJ, Hamelinck C, Hauer AD, Hoftijzer D, Monnink SH, Schipper JC, Constandse JC, Peters NS, Lip GY, Steinhubl SR. Ambulatory atrial fibrillation detection and quantification by wristworn AI device compared to standard holter monitoring. npj Digital Medicine. 2025 Mar 25;8(1):177. link
Lin CH, Liu ZY, Chu PH, Chen JS, Wu HH, Wen MS, Kuo CF, Chang TY. A multitask deep learning model utilizing electrocardiograms for major cardiovascular adverse events prediction. npj Digital Medicine. 2025 Jan 2;8(1):1. link
Zhang J, Wang W, Dong J, Yang X, Bai S, Tian J, Li B, Li X, Zhang J, Wu H, Zeng X. Rapid vessel segmentation and reconstruction of head and neck angiograms from MR vessel wall images. npj Digital Medicine. 2025 Jul 28;8(1):483. link
Duffy G, Clarke SL, Christensen M, He B, Yuan N, Cheng S, Ouyang D. Confounders mediate AI prediction of demographics in medical imaging. NPJ digital medicine. 2022 Dec 22;5(1):188. link
Mao X, Huang Y, Jin Y, Wang L, Chen X, Liu H, Yang X, Xu H, Luan X, Xiao Y, Feng S. A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs. npj Digital Medicine. 2025 Jan 28;8(1):68. link
Wu C, Lima EA, Stowers CE, Xu Z, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. MRI-based digital twins to improve treatment response of breast cancer by optimizing neoadjuvant chemotherapy regimens. npj Digital Medicine. 2025 Apr 7;8(1):195. link
Rogers AJ, Bhatia NK, Bandyopadhyay S, Tooley J, Ansari R, Thakkar V, Xu J, Soto JT, Tung JS, Alhusseini MI, Clopton P. Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram. npj Digital Medicine. 2025 Jan 11;8(1):21. link
Pei Y, Wang G, Cao H, Jiang S, Wang D, Wang H, Wang H, Yu H. A deep-learning pipeline to diagnose pediatric intussusception and assess severity during ultrasound scanning: a multicenter retrospective-prospective study. NPJ Digital Medicine. 2023 Sep 30;6(1):182. link
Zhong Z, Wang Y, Wu J, Hsu WC, Somasundaram V, Bi L, Kulkarni S, Ma Z, Collins S, Baird G, Ahn SH. Vision-language model for report generation and outcome prediction in CT pulmonary angiogram. NPJ Digital Medicine. 2025 Jul 12;8(1):432. link
Wang S, Li G, Gao M, Zhuo L, Liu M, Ma Z, Zhao W, Fu X. GH-UNet: group-wise hybrid convolution-VIT for robust medical image segmentation. npj Digital Medicine. 2025 Jul 10;8(1):426. link
Mason F, Pandey AC, Gadaleta M, Topol EJ, Muse ED, Quer G. AI-enhanced reconstruction of the 12-lead electrocardiogram via 3-leads with accurate clinical assessment. NPJ Digital Medicine. 2024 Aug 1;7(1):201. link
Khunte A, Sangha V, Oikonomou EK, Dhingra LS, Aminorroaya A, Mortazavi BJ, Coppi A, Brandt CA, Krumholz HM, Khera R. Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices. npj Digital Medicine. 2023 Jul 11;6(1):124. link
Avram R, Olgin JE, Ahmed Z, Verreault-Julien L, Wan A, Barrios J, Abreau S, Wan D, Gonzalez JE, Tardif JC, So DY. CathAI: fully automated coronary angiography interpretation and stenosis estimation. npj Digital Medicine. 2023 Aug 11;6(1):142. link
Speranza G, Mischkewitz S, Al-Noor F, Kainz B. Value of clinical review for AI-guided deep vein thrombosis diagnosis with ultrasound imaging by non-expert operators. npj Digital Medicine. 2025 Mar 1;8(1):135. link
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
Agasthi P, Kanmanthareddy A, Khalil C, Egbuche O, Yarlagadda V, Sachdeva R, Arsanjani R. Comparison of computed tomography derived fractional flow reserve to invasive fractional flow reserve in diagnosis of functional coronary stenosis: a meta-analysis. Scientific Reports. 2018 Aug 1;8(1):11535. link
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
Xie J, Juan YH, Wang Q, Chen J, Zhuang J, Xie Z, Liang C, Zhu Y, Yu Z, Li J, Saboo SS. Evaluation of left pulmonary artery sling, associated cardiovascular anomalies, and surgical outcomes using cardiovascular computed tomography angiography. Scientific reports. 2017 Jan 5;7(1):40042. link
Tay SY, Chang PY, Lao WT, Lin YC, Chung YH, Chan WP. The proper use of coronary calcium score and coronary computed tomography angiography for screening asymptomatic patients with cardiovascular risk factors. Scientific reports. 2017 Dec 15;7(1):17653. link
Pham TD, Watanabe Y, Higuchi M, Suzuki H. Texture analysis and synthesis of malignant and benign mediastinal lymph nodes in patients with lung cancer on computed tomography. Scientific reports. 2017 Feb 24;7(1):43209. link
Li R, Cai P, Ma KS, Ding SY, Guo DY, Yan XC. Dynamic enhancement patterns of intrahepatic cholangiocarcinoma in cirrhosis on contrast-enhanced computed tomography: risk of misdiagnosis as hepatocellular carcinoma. Scientific reports. 2016 May 26;6(1):26772. link
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
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Momeni A, Rahmani B, Malléjac M, Del Hougne P, Fleury R. Backpropagation-free training of deep physical neural networks. Science. 2023 Dec 15;382(6676):1297-303. link
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George D, Lehrach W, Kansky K, Lázaro-Gredilla M, Laan C, Marthi B, Lou X, Meng Z, Liu Y, Wang H, Lavin A. A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs. Science. 2017 Dec 8;358(6368):eaag2612. link
Bashivan P, Kar K, DiCarlo JJ. Neural population control via deep image synthesis. Science. 2019 May 3;364(6439):eaav9436. link
Costello TH, Pennycook G, Rand DG. Durably reducing conspiracy beliefs through dialogues with AI. Science. 2024 Sep 13;385(6714):eadq1814. link
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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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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
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Findling C, Wyart V. Computation noise promotes zero-shot adaptation to uncertainty during decision-making in artificial neural networks. Science Advances. 2024 Oct 30;10(44):eadl3931. link
Li S, Wang H, Ma W, Qiu L, Xia K, Zhang Y, Lu H, Zhu M, Liang X, Wu XE, Liang H. Monitoring blood pressure and cardiac function without positioning via a deep learning–assisted strain sensor array. Science Advances. 2023 Aug 11;9(32):eadh0615. link
Daneshjou R, Vodrahalli K, Novoa RA, Jenkins M, Liang W, Rotemberg V, Ko J, Swetter SM, Bailey EE, Gevaert O, Mukherjee P. Disparities in dermatology AI performance on a diverse, curated clinical image set. Science advances. 2022 Aug 12;8(31):eabq6147. link
Du W, Zhang L, Suh E, Lin D, Marcus C, Ozkan L, Ahuja A, Fernandez S, Shuvo II, Sadat D, Liu W. Conformable ultrasound breast patch for deep tissue scanning and imaging. Science Advances. 2023 Jul 28;9(30):eadh5325. link
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
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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
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
Zhou H, Zhou F, Chen H. Cohort-individual cooperative learning for multimodal cancer survival analysis. IEEE Transactions on Medical Imaging. 2024 Sep 6. link
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
Siebert H, Großbröhmer C, Hansen L, Heinrich MP. Convexadam: Self-configuring dual-optimisation-based 3d multitask medical image registration. IEEE Transactions on Medical Imaging. 2024 Sep 16. link
Huang W, Hu J, Xiao J, Wei Y, Bi X, Xiao B. Prototype-guided graph reasoning network for few-shot medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Sep 13. link
Kadry K, Olender ML, Schuh A, Karmakar A, Petersen K, Schaap M, Marlevi D, UpdePac A, Mizukami T, Taylor C, Edelman ER. Morphology-based non-rigid registration of coronary computed tomography and intravascular images through virtual catheter path optimization. IEEE transactions on medical imaging. 2024 Oct 7. link
Zhang R, Mo H, Wang J, Jie B, He Y, Jin N, Zhu L. UTSRMorph: a unified transformer and superresolution network for unsupervised medical image registration. IEEE Transactions on Medical Imaging. 2024 Sep 25. link
Zhang J, Pei J, Xu D, Jin Y, Heng PA. DC 2 T: Disentanglement-Guided Consolidation and Consistency Training for Semi-Supervised Cross-Site Continual Segmentation. IEEE Transactions on Medical Imaging. 2024 Sep 27. link
You X, He J, Yang J, Gu Y. Learning with explicit shape priors for medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Sep 27. link
Liu Y, Tian Y, Wang C, Chen Y, Liu F, Belagiannis V, Carneiro G. Translation consistent semi-supervised segmentation for 3d medical images. IEEE Transactions on Medical Imaging. 2024 Sep 26. link
Chen H, Cai Y, Wang C, Chen L, Zhang B, Han H, Guo Y, Ding H, Zhang Q. Multi-organ foundation model for universal ultrasound image segmentation with task prompt and anatomical prior. IEEE Transactions on Medical Imaging. 2024 Oct 3. link
Chi J, Sun Z, Meng L, Wang S, Yu X, Wei X, Yang B. Low-dose CT image super-resolution with noise suppression based on prior degradation estimator and self-guidance mechanism. IEEE Transactions on Medical Imaging. 2024 Sep 4. link
Shen C, Zhu H, Zhou Y, Liu Y, Yi S, Dong L, Zhao W, Brady DJ, Cao X, Ma Z, Lin Y. Continuous 3D Myocardial Motion Tracking via Echocardiography. IEEE Transactions on Medical Imaging. 2024 Jun 27;43(12):4236-52. link
Xu C, Zhang T, Zhang D, Zhang D, Han J. Deep generative adversarial reinforcement learning for semi-supervised segmentation of low-contrast and small objects in medical images. IEEE Transactions on Medical Imaging. 2024 Apr 1;43(9):3072-84. link
Wu J, Guo D, Wang G, Yue Q, Yu H, Li K, Zhang S. FPL+: Filtered pseudo label-based unsupervised cross-modality adaptation for 3D medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Apr 11;43(9):3098-109. link
Chen X, Zhou B, Guo X, Xie H, Liu Q, Duncan JS, Sinusas AJ, Liu C. DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT. IEEE transactions on medical imaging. 2024 Apr 5;43(9):3110-25. link
Han B, Sun L, Li C, Yu Z, Jiang W, Liu W, Tao D, Liu B. Deep location soft-embedding-based network with regional scoring for mammogram classification. IEEE Transactions on Medical Imaging. 2024 Apr 16;43(9):3137-48. link
Ye S, Xu Y, Chen D, Han S, Liao J. Learning a single network for robust medical image segmentation with noisy labels. IEEE Transactions on Medical Imaging. 2024 Apr 18;43(9):3188-99. link
Chen Y, Gao Y, Zhu L, Shao W, Lu Y, Han H, Xie Z. PCNet: Prior category network for CT universal segmentation model. IEEE Transactions on Medical Imaging. 2024 Apr 30;43(9):3319-30. link
Wu J, Zhang Y, Fang H, Duan L, Tan M, Yang W, Wang C, Liu H, Jin Y, Xu Y. Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle. IEEE Transactions on Medical Imaging. 2024 Apr 26;43(9):3331-42. link
Shaker A, Maaz M, Rasheed H, Khan S, Yang MH, Khan FS. UNETR++: delving into efficient and accurate 3D medical image segmentation. IEEE Transactions on Medical Imaging. 2024 May 9;43(9):3377-90. link
Jiang X, Missel R, Toloubidokhti M, Gillette K, Prassl AJ, Plank G, Horáček BM, Sapp JL, Wang L. Hybrid neural state-space modeling for supervised and unsupervised electrocardiographic imaging. IEEE Transactions on Medical Imaging. 2024 Mar 13;43(8):2733-44. link
Wang Z, Yang Y, Chen Y, Yuan T, Sermesant M, Delingette H, Wu O. Mutual information guided diffusion for zero-shot cross-modality medical image translation. IEEE Transactions on Medical Imaging. 2024 Mar 29;43(8):2825-38. link
Mineo R, Salanitri FP, Bellitto G, Kavasidis I, De Filippo O, Millesimo M, De Ferrari GM, Aldinucci M, Giordano D, Palazzo S, D’Ascenzo F. A convolutional-transformer model for ffr and ifr assessment from coronary angiography. IEEE Transactions on Medical Imaging. 2024 Jul 2;43(8):2866-77. link
Cui H, Li Y, Wang Y, Xu D, Wu LM, Xia Y. Toward accurate cardiac MRI segmentation with variational autoencoder-based unsupervised domain adaptation. IEEE Transactions on Medical Imaging. 2024 Mar 28;43(8):2924-36. link
Huang X, Huang J, Zhao K, Zhang T, Li Z, Yue C, Chen W, Wang R, Chen X, Zhang Q, Fu Y. Sasan: Spectrum-axial spatial approach networks for medical image segmentation. IEEE Transactions on Medical Imaging. 2024 Apr 1;43(8):3044-56. link
Chaudhary MF, Gerard SE, Christensen GE, Cooper CB, Schroeder JD, Hoffman EA, Reinhardt JM. LungViT: ensembling cascade of texture sensitive hierarchical vision transformers for cross-volume chest CT image-to-image translation. IEEE transactions on medical imaging. 2024 Feb 19;43(7):2448-65. link
Li L, Camps J, Wang ZJ, Beetz M, Banerjee A, Rodriguez B, Grau V. Toward enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference. IEEE transactions on medical imaging. 2024 Feb 19;43(7):2466-78. link
Hou Q, Wang Y, Cao P, Cheng S, Lan L, Yang J, Liu X, Zaiane OR. A collaborative self-supervised domain adaptation for low-quality medical image enhancement. IEEE Transactions on Medical Imaging. 2024 Feb 19;43(7):2479-94. 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
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Koetzier LR, Wu J, Mastrodicasa D, Lutz A, Chung M, Koszek WA, Pratap J, Chaudhari AS, Rajpurkar P, Lungren MP, Willemink MJ. Generating synthetic data for medical imaging. Radiology. 2024 Sep 10;312(3):e232471. link
Marcinkiewicz AM, Buchwald M, Shanbhag A, Bednarski BP, Killekar A, Miller RJ, Builoff V, Lemley M, Berman DS, Dey D, Slomka PJ. AI for multistructure incidental findings and mortality prediction at chest CT in lung cancer screening. Radiology. 2024 Sep 17;312(3):e240541. link
Sverzellati N, Milanese G, Ryerson CJ, Hatabu H, Walsh SL, Papapietro VR, Gazzani SE, Bacchini E, Specchia F, Marrocchio C, Milone F. Interstitial Lung Abnormalities on Unselected Abdominal and Thoracoabdominal CT Scans in 21 118 Patients. Radiology. 2024 Nov 19;313(2):e233374. link
Bhatt SP, Nakhmani A, Sthanam V, Kizhakke Puliyakote A, Reinhardt JM, Bodduluri S. PiSlope: a new CT metric for quantifying airway remodeling in chronic obstructive pulmonary disease. Radiology. 2024 Nov 26;313(2):e240717. link
Zhong D, Sidorenkov G, Jacobs C, de Jong PA, Gietema HA, Stadhouders R, Nackaerts K, Aerts JG, Prokop M, Groen HJ, de Bock GH. Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial. Radiology. 2024 Oct 22;313(1):e240535. link
Nissan N, Comstock CE, Sevilimedu V, Gluskin J, Mango VL, Hughes M, Ochoa-Albiztegui RE, Sung JS, Jochelson MS. Diagnostic accuracy of screening contrast-enhanced mammography for women with extremely dense breasts at increased risk of breast cancer. Radiology. 2024 Oct 1;313(1):e232580. link
Gommers JJ, Verboom SD, Duvivier KM, van Rooden JK, van Raamt AF, Houwers JB, Naafs DB, Duijm LE, Abbey CK, Webster MA, Broeders MJ. Enhancing radiologist reading performance by ordering screening mammograms based on characteristics that promote visual adaptation. Radiology. 2024 Oct 8;313(1):e240237. 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
Brunet J, Cook AC, Walsh CL, Cranley J, Tafforeau P, Engel K, Arthurs O, Berruyer C, Burke O’Leary E, Bellier A, Torii R. Multidimensional analysis of the adult human heart in health and disease using hierarchical phase-contrast tomography. Radiology. 2024 Jul 16;312(1):e232731. link
Abdollahi A, Kato Y, Bakhshi H, Varadarajan V, Chehab O, Zeitoun R, Ostovaneh MR, Wu CO, Bertoni AG, Shah SJ, Ambale-Venkatesh B. Differential stroke volume between left and right ventricles as a predictor of clinical outcomes: The MESA study. Radiology. 2024 Jul 23;312(1):e232973. link
Suh PS, Shim WH, Suh CH, Heo H, Park CR, Eom HJ, Park KJ, Choe J, Kim PH, Park HJ, Ahn Y. Comparing diagnostic accuracy of radiologists versus GPT-4V and Gemini Pro Vision using image inputs from diagnosis please cases. Radiology. 2024 Jul 9;312(1):e240273. link
Rosenkrantz AB, Cummings RW. Radiologist workforce attrition from 2019 to 2024: a national Medicare analysis. Radiology. 2024 Jul 23;312(1):e240632. link
Tejani AS, Cook TS, Hussain M, Sippel Schmidt T, O’Donnell KP. Integrating and adopting AI in the radiology workflow: a primer for standards and integrating the healthcare enterprise (IHE) profiles. Radiology. 2024 Jun 18;311(3):e232653. link
Lauritzen AD, Lillholm M, Lynge E, Nielsen M, Karssemeijer N, Vejborg I. Early indicators of the impact of using AI in mammography screening for breast cancer. Radiology. 2024 Jun 4;311(3):e232479. link
Bhayana R, Nanda B, Dehkharghanian T, Deng Y, Bhambra N, Elias G, Datta D, Kambadakone A, Shwaartz CG, Moulton CA, Henault D. Large language models for automated synoptic reports and resectability categorization in pancreatic cancer. Radiology. 2024 Jun 18;311(3):e233117. link
Lin C, Tsai DJ, Wang CC, Chao YP, Huang JW, Lin CS, Fang WH. Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial. Radiology. 2024 Jun 25;311(3):e231937. link
Dudurych I, Pelgrim GJ, Sidorenkov G, Garcia-Uceda A, Petersen J, Slebos DJ, de Bock GH, van den Berge M, de Bruijne M, Vliegenthart R. Low-dose CT–derived bronchial parameters in individuals with healthy lungs. Radiology. 2024 Jun 25;311(3):e232677. link
Garzelli L, Dufay R, Tual A, Corcos O, Cazals-Hatem D, Vilgrain V, Nuzzo A, Ben Abdallah I, Ronot M. Predictors of Survival without Intestinal Resection after First-Line Endovascular revascularization in patients with Acute arterial mesenteric ischemia. Radiology. 2024 Jun 11;311(3):e230830. link
Nguyen DL, Ren Y, Jones TM, Thomas SM, Lo JY, Grimm LJ. Patient characteristics impact performance of AI algorithm in interpreting negative screening digital breast tomosynthesis studies. Radiology. 2024 May 21;311(2):e232286. link
Zhou Y, Ong H, Kennedy P, Wu CC, Kazam J, Hentel K, Flanders A, Shih G, Peng Y. Evaluating GPT-4V (GPT-4 with vision) on detection of radiologic findings on chest radiographs. Radiology. 2024 May 7;311(2):e233270. link
Krishna S, Bhambra N, Bleakney R, Bhayana R. Evaluation of reliability, repeatability, robustness, and confidence of GPT-3.5 and GPT-4 on a radiology board–style examination. Radiology. 2024 May 21;311(2):e232715. link
Dai C, Xiong Y, Zhu P, Yao L, Lin J, Yao J, Zhang X, Huang R, Wang R, Hou J, Wang K. Deep learning assessment of small renal masses at contrast-enhanced multiphase CT. Radiology. 2024 May 14;311(2):e232178. link
Na KJ, Kim YT, Goo JM, Kim H. Clinical utility of a CT-based AI prognostic model for segmentectomy in non–small cell lung cancer. Radiology. 2024 Apr 16;311(1):e231793. link
Choi B, Díaz AA, San José Estépar R, Enzer N, Castro V, Han MK, Washko GR, San José Estépar R, Ash SY, COPDGene Study. Association of Acute Respiratory Disease Events with Quantitative Interstitial Abnormality Progression at CT in Individuals with a History of Smoking. Radiology. 2024 Apr 30;311(1):e231801. link
Pan Z, Hu G, Zhu Z, Tan W, Han W, Zhou Z, Song W, Yu Y, Song L, Jin Z. Predicting invasiveness of lung adenocarcinoma at chest CT with deep learning ternary classification models. Radiology. 2024 Apr 9;311(1):e232057. link
Liu Y, Sorkhei M, Dembrower K, Azizpour H, Strand F, Smith K. Use of an AI score combining cancer signs, masking, and risk to select patients for supplemental breast cancer screening. Radiology. 2024 Apr 9;311(1):e232535. link
Berg WA, Berg JM, Bandos AI, Vargo A, Chough DM, Lu AH, Ganott MA, Kelly AE, Nair BE, Hartman JY, Waheed U. Addition of contrast-enhanced mammography to tomosynthesis for breast cancer detection in women with a personal history of breast cancer: prospective TOCEM trial interim analysis. Radiology. 2024 Apr 30;311(1):e231991. link
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