Publications

Journal papers

[134] Msamra M, Sobarzo A, Elkin R, Agbaria A, Appel D, Natour S, Davidesko S, Meirovitz M, Oh JH, Delgado B, Norton L, and Kessous R. Tumor-Intrinsic Transcriptional Programs Influence Engraftment of High-Grade Serous Ovarian Carcinoma Patient-Derived Xenografts. Scientific Reports, Accepted, 2026. 

[133] Diplas BH, Brown DN, Pei X, Zhu Y, Novaj A, Han J, Shamseddine A, Paudyal R, Aliotta E, Graybill C, Korn WM, Westheimer E, Morris LGT, Wong RJ, McBride SM, Ho AL, Oh JH, Schöder H, Hatzoglou V, Shukla-Dave A, Sherman EJ, Razavi P, Humm JL, Daber RD, Katabi N, Reis-Filho JS, Weigelt B, Lee NY, and Riaz N. Intra-treatment ctDNA and imaging dynamics identify candidates for adaptive therapy in HPV-related oropharyngeal cancer. Nature Communications, Accepted, 2026. 

[132] Apte AP, LoCastro E, Iyer A, Elguindi S, Jiang J, Oh JH, Veeraraghavan H, Shukla-Dave A, and Deasy JO. Artificial Intelligence Apps for Medical Image Analysis using pyCERR and Cancer Genomics Cloud. Medical Physics, Accepted, 2026. 

[131] Treechairusame T, Zhang P, Hu YC, Aliotta E, Li A, Aristophanous M, Cervino L, Deasy JO, Lee NY, Oh JH*, and Zhang P*. Early salivary gland shrinkage is associated with an increased risk of acute xerostomia in head and neck cancer radiotherapy. Advances in Radiation Oncology. 11(8):102090, 2026. [Co-senior author] 

[130] Oh JH, Auer P, Hall W, Rosenstein BS, Deasy JO, and Kerns S. Deep learning on genome-wide association studies to predict the patient-specific risk of radiation-induced erectile dysfunction. Radiotherapy and Oncology. 219:111531, 2026. 

[129] Firestone R, Simhal A, Akhlaghi T, Oh JH, McAvoy D, Maclachlan K, Garces JJ, Mailankody S, Hassoun H, Shah U, Korde N, Tan CS, Rajeeve S, Hashmi H, Lesokhin A, Hosszu K, Maura F, Deasy JO, Usmani S, and Hultcrantz M. A differentiated effector T cell repertoire defines a functionally high-risk group of smoldering myeloma patients. Blood Cancer Journal. 16(1):67, 2026.  

[128] Naderi E, Watt GP, Knight JA, Malone KE, Lynch CF, John EM, Shu X, Nguyen TL, Oh JH, Woods M, Liang X, Derkach A, Pike MC, and Bernstein JL. Does a Mammographic Density Polygenic Risk Score Improve Risk Models for Contralateral Breast Cancer?. Scientific Reports. 16(1):12125, 2026. 

[127] Lee S, Shu X, Derkach A, Reiner AS, Liang X, Woods M, Concannon P, Lynch CF, Malone KE, Knight JA, John EM, Deasy JO, Bernstein JL, and Oh JH. Integrating genomic and non-genomic data to predict contralateral breast cancer after radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 125(5):1512-1521, 2026. 

[126] Lee D, Hu YC, TreeChairusame T, Oh JH, Lee N, Aristophanous M, Cerviño L, and Zhang P. Deep Learning-Based Head and Neck Deformable Image Registration Using Spatio-Temporal Analysis and Self Attention. Physics and Imaging in Radiation Oncology. 37:100928, 2026. 

[125] Duong S, Lee D, Glide-Hurst C, Paliwal B, Crosby J, Boss M, Cui Y, Huang M, Li H, Sheikh K, Kim T, Monroe J, Oh JH, Xiao Y, and Sohn JW. Multi-Institutional MRI-Based Radiomic Pilot Study to Measure the Variations Between Scanner Vendors and Imaging Sessions. Frontiers in Oncology. 16:1686601, 2026.  

[124] Oh JH, Apte AP, Veeraraghavan H, Zhu J, Shukla-Dave A, and Deasy JO. Radiomic clustering using graph network techniques coupled with unbalanced optimal transport. Computational and Structural Biotechnology Journal. 27:4772-4778, 2025.  

[123] Han JE, Diplas BH, Paudyal R, Oh JH, Deasy JO, Sherman E, Schoder H, Hatzoglou V, Wong RJ, Wray R, Boyle J, Grkovski M, Humm JL, Riaz N, Shukla-Dave A, and Lee N. Apparent Diffusion Coefficient MRI as a Predictive Biomarker for Hypoxia, Treatment De-escalation, and Recurrence in HPV-Associated Oropharyngeal Cancer. International Journal of Radiation Oncology*Biology*Physics. 124(4):1015-1023, 2026. 

[122] Treechairusame T, Singh A, Dee EC, Zhang P, Oh JH, Xiong J, Aliotta E, Gelblum D, Yu Y, McBride S, Safavi AH, Wu Y, Caineng C, Wong W, Dunn L, Michel L, Huryn J, Ganly I, Cracchiolo J, Wong R, Estilo C, Lee N. Osteoradionecrosis as a Complication Following Intensity-Modulated Radiation Therapy or Proton Therapy in the Treatment of Oral Cavity Cancer. Oral Oncology. 168:107581, 2025. 

[121] Watt GP, Reiner AS, Shu X, Malone KE, Knight JA, John EM, Chow EJ, Lynch CF, Mellemkjær L, Woods M, Liang X, Tran AP, Oh JH, Derkach A, and Bernstein JL. Polygenic risk of coronary artery disease for long-term survivors of breast cancer. JNCI: Journal of the National Cancer Institute. 117(10):2073-2081, 2025. 

[120] Oh JH, Rizzuto G, Elkin R, Weistuch C, Norton L, Dveksler G, and Deasy JO. Pregnancy- specific glycoproteins as potential drug targets for female lung adenocarcinoma patients. Briefings in Functional Genomics. 24:elaf004, 2025.  

[119] Simhal AK, Weistuch C, Murgas K, Grange D, Zhu J, Oh JH, Elkin R, and Deasy JO. ORCO: Ollivier-Ricci Curvature-Omics — an unsupervised method for analyzing robustness in biological systems. Bioinformatics. btaf093, 2025. 

[118] Oh JH, Pareja F, Elkin R, Xu K, Norton L, and Deasy JO. Biological correlates associated with high-risk breast cancer patients identified using a computational method. npj Breast Cancer. 11(1):8, 2025.

[117] Simhal AK, Firestone R, Oh JH, Avutu V, Norton L, Hultcrantz M, Usmani SZ, Maclachlan KH, and Deasy JO. High WEE1 expression is independently linked to poor survival in multiple myeloma. Blood Cancer. 15(1):22, 2025.  

[116] Zhang P, Happersett L, Burleson S, Oh JH, Elsayegh A, Leong B, Thor M, Damato A, Jackson A, Cervino L, Deasy JO, and Zelefsky M. Reduction of late urinary toxicity from prostate cancer radiotherapy via intrafractional MV-kV image guidance. International Journal of Radiation Oncology*Biology*Physics. 121(1):261-268, 2025. 

[115] Aliotta E, Paudyal R, Diplas B, Han J, Hu YC, Oh JH, Hatzoglou V, Jensen N, Zhang P, Aristophanous M, Riaz N, Deasy JO, Lee NY, and Shukla-Dave A. Multi-modality Imaging Parameters that Predict Rapid Tumor Regression in Head and Neck Radiotherapy. Physics and Imaging in Radiation Oncology. 31:100603, 2024.

[114] Sun X, Verma SP, Jia G, Wang X, Ping J, Guo X, Shu XO, Chen J, Derkach A, Cai Q, Liang X, Long J, Offit K, Oh JH, Reiner A, Watt G, Woods M, Yang Y, Ambrosone C, Ambs S, Chen Y, Concannon P, Garcia-Closas M, Gu J, Haiman C, Hu J, Huo D, John E, Knight J, Li C, Lynch C, Mellemkjaer L, Nathanson K, Nemesure B, Olopade O, Olshan A, Pal T, Palmer J, Press M, Sanderson M, Sandler D, Troester M, Zheng W, Bernstein J, Buas M, and Shu X. Case-case genome-wide analyses identify subtype-informative variants that confer risk for triple negative breast cancer. Cancer Research. 84(15):2533-2548, 2024.

[113] Sun X, Reiner AS, Tran AP, Watt GP, Oh JH, Mellemkjær L, Lynch CF, Knight JA, John EM, Malone KE, Liang X, Woods M, Derkach A, Concannon P, Bernstein JL, and Shu X. A genome-wide association study of contralateral breast cancer in the Women's Environmental Cancer and Radiation Epidemiology Study. Breast Cancer Research. 26(1):16, 2024.

[112] Choi W, Liu CJ, Riyahi Alam S, Oh JH, Vaghjiani R, Humm J, Weber W, Adusumilli PS, Deasy JO, and Lu W. Preoperative 18F-FDG PET/CT and CT Radiomics for Identifying Aggressive Histopathological Subtypes in Early Stage Lung Adenocarcinoma. Computational and Structural Biotechnology Journal. 21:5601-5608, 2023.

[111] Thor M, Fitzgerald K, Apte A, Oh JH, Iyer A, Odiase O, Nadeem S, Yorke ED, Chaft J, Wu AJ, Offin M, Simone II CB, Preeshagul I, Gelblum DY, Gomez D, Deasy JO, and Rimner A.Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation. Radiotherapy and Oncology. 190:109983, 2023.

[110] Simhal A, Maclachlan K, Elkin R, Zhu J, Norton L, Deasy JO, Oh JH, Usmani S, and Tannenbaum A. Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival. Blood Cancer. 13(1):175, 2023.

[109] Elkin R, Oh JH, Dela Cruz F, Norton L, Deasy JO, Kung AL, and Tannenbaum A. Dynamic Network Curvature Analysis of Gene Expression Reveals Novel Potential Therapeutic Targets in Sarcoma. Scientific Reports. 14(1):488, 2023.

[108] Zhu J, Veeraraghavan H, Jiang J, Oh JH, Norton L, Deasy JO, and Tannenbaum A. Wasserstein HOG: Local Directionality Extraction via Optimal Transport. IEEE Transactions on Medical Imaging. 43(3):916-927, 2024.

[107] Oh JH, Tannenbaum A, and Deasy JO. Improved prediction of drug-induced liver injury literature using natural language processing and machine learning methods. Frontiers in Genetics. 14:1161047, 2023.

[106] Zhu J, Oh JH, Simhal AK, Elkin R, Norton L, Deasy JO, and Tannenbaum A. Geometric Graph Neural Networks on Multi-omics Data to Predict Cancer Survival Outcomes. Computers in Biology and Medicine. 163:107117, 2023.

[105] Oh JH, Lee S, Thor M, Rosenstein BS, Tannenbaum A, Kerns S, and Deasy JO. Predicting the germline dependence of hematuria risk in prostate cancer radiotherapy patients. Radiotherapy and Oncology. 185:109723, 2023.

[104] Kang M and Oh JH. Editorial of Special Issue "Deep Learning and Machine Learning in Bioinformatics". International Journal of Molecular Sciences. 23(12):6610, 2022.

[103] Zhu J*, Oh JH*, Deasy JO, and Tannenbaum A. vWCluster: Vector-Valued Optimal Transport for Network Based Clustering Using Multi-omics Data in Breast Cancer. PLoS ONE. 17(3): e0265150, 2022. [Co-first author]

[102] Pouryahya M*, Oh JH*, Mathews JC, Belkhatir Z, Moosmüller C, Deasy JO and Tannenbaum AR. Pan-cancer Prediction of Cell Line-Drug Sensitivity Using Network Based Methods. International Journal of Molecular Sciences. 23(3): 1074, 2022. [Co-first and corresponding author]

[101] Elkin R*, Oh JH*, Liu Y, Selenica P, Weigelt B, Reis-Filho J, Zamarin D, Deasy JO, Norton L, and Levine A. Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint Inhibitors. NPJ Genomic Medicine. 6(1):99, 2021. [Co-first author]

[100] Paudyal R, LoCastro E, Reyngold M, Do RK, Konar AS, Oh JH, Dave A, Yu K, Goodman KA, and Shukla-Dave A. Longitudinal monitoring of simulated interstitial fluid pressure for pancreatic ductal adenocarcinoma patients treated with stereotactic body radiotherapy. Cancers. 13(17):4319, 2021.

[99] Paudyal R, Grkovski M, Oh JH, Schöder H, Aramburu Nunez D, Hatzoglou V, Deasy JO, Humm JL, Shukla-Dave A, and Lee NY. Application of community detection algorithm to investigate the correlation between imaging biomarkers of tumor metabolism, hypoxia, cellularity, and perfusion for precision radiotherapy in head and neck squamous cell carcinomas. Cancers. 13(15):3908, 2021.

[98] Mahmood U, Apte A, Kanan C, Bates DDB, Corrias G, Manneli L, Oh JH, Erdi YE, Nguyen J, Deasy JO, and Shukla-Dave A. Quality control of radiomic features using 3D printed CT phantoms. Journal of Medical Imaging. 8(3):033505, 2021.

[97] Oh JH, Choi W, Ko E, Kang M, Tannenbaum A, and Deasy JO. PathCNN: Interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma. Bioinformatics (ISMB 2021). 37(Supplement_1):i443-i450, 2021.

[96] Oh JH, Apte AP, Katsoulakis E, Riaz N, Hatzoglou V, Yu Y, Mahmood U, Veeraraghavan H, Pouryahya M, Iyer A, Shukla-Dave A, Tannenbaum A, Lee NY, and Deasy JO. Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering. Journal of Medical Imaging. 8(3):031904, 2021.

[95] Paudyal R, Chen L, Oh JH, Zakeri K, Hatzoglou V, Tsai CJ, Lee N, and Shukla-Dave A. Nongaussian intravoxel incoherent motion diffusion weighted and fast exchange regime dynamic contrast-enhanced-MRI of Nasopharyngeal Carcinoma: Preliminary study for predicting locoregional failure. Cancers.13(5):1128, 2021.

[94] Shah AD, Konar AS, Paudyal R, Oh JH, LoCastro E, Nunez DA, Swinburne N, Vachha B, Ulaner GA, Young RJ, Holodny AI, Beal K, Shukla-Dave A, and Hatzoglou V. Diffusion and perfusion MRI predicts response preceding and shortly after radiosurgery to brain metastases: a pilot study. Journal of Neuroimaging. 31(2):317-323, 2021.

[93] Oh JH, Tannenbaum A, and Deasy JO. Identification of biological correlates associated with respiratory failure in COVID-19. BMC Medical Genomics. 13(1):186, 2020.

[92] Zhu J, Elkin R, Oh JH, Deasy JO, and Tannenbaum A. A Vectorial Approach to Unbalanced Optimal Mass Transport. IEEE Access. 8:209224-209231, 2020.

[91] Pouryahya M, Oh JH, Javanmard P, Mathews JC, Belkhatir Z, Deasy JO, and Tannenbaum AR. aWCluster: A Novel Integrative Network-based Clustering of Multiomics for Subtype Analysis of Cancer Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(3):1472-148, 2022.

[90] Park KS, Kim SH, Oh JH, and Kim SY. Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning. Briefings in Bioinformatics. 22(4):bbaa336, 2020.

[89] von Reibnitz D, Yorke ED, Oh JH*, Apte AP, Yang J, Pham H, Thor M, Wu AJ, Fleisher M, Gelb E, Deasy JO, and Rimner A. Predictive modeling of thoracic radiotherapy toxicity and the potential role of serum alpha-2-macroglobulin. Frontiers in Oncology. 10:1395, 2020. [Corresponding author]

[88] Katsoulakis E, Yu Y, Apte AP, Leeman JE, Katabi N, Morris L, Deasy JO, Chan TA, Lee NY, Riaz N, Hatzoglou V, and Oh JH. Radiomic analysis identifies tumor subtypes associated with distinct molecular and microenvironmental factors in head and neck squamous cell carcinoma. Oral Oncology. 110:104877, 2020.

[87] Lee S, Deasy JO, Oh JH, Di Meglio A, Dumas A, Menvielle G, Charles C, Boyault S, Rousseau M, Besse C, Thomas E, Boland A, Cottu P, Tredan O, Levy C, Martin AL, Everhard S, Ganz PA, Partridge A, Michiels S, Deleuze JF, Andre F, and Vaz-Luis I. Prediction of Breast Cancer Treatment-Induced Fatigue by Machine Learning Using Genome Wide Association Data. JNCI Cancer Spectrum. 4(5): pkaa039, 2020.

[86] Thor M, Deasy JO, Hu C, Gore E, Bar-Ad V, Robinson C, Wheatley M, Oh JH, Bogart J, Garces Y, Kavadi V, Narayan S, Iyengar P, Witt J, Welsh J, Koprowski C, Larner J, Xiao Y, and Bradley J. Modeling the impact of cardio-pulmonary irradiation on overall survival in NRG Oncology trial RTOG 0617. Clinical Cancer Research. 26(17):4643-4650, 2020.

[85] Thor M, Oh JH, Apte AP, and Deasy JO. Registering Study Analysis Plans (SAPs) Before Dissecting Your Data-Updating and Standardizing Outcome Modeling. Frontiers in Oncology. 10:978, 2020.

[84] Konar AS, Fung M, Paudyal R, Oh JH, Mazaheri Y, Hatzoglou V, and Shukla-Dave A. Diffusion-Weighted Echo Planar Imaging using MUltiplexed Sensitivity Encoding and Reverse Polarity Gradient in Head and Neck Cancer: An Initial Study. Tomography. 6(2):231-240, 2020.

[83] Swinburne N, LoCastro E, Paudyal R, Oh JH, Taunk N, Shah A, Beal K, Vachha BA, Young RJ, Holodny A, Shukla-Dave A, and Hatzoglou V. Computational modeling of interstitial fluid pressure and velocity in non-small cell lung cancer brain metastases treated with stereotactic radiosurgery. Frontiers in Neurology. 11:402, 2020.

[82] Apte AP, Iyer A, Thor M, Pandya R, Haq R, Jiang J, LoCastro E, Shukla-Dave A, Sasankan N, Xiao Y, Yu-Chi H, Elguindi S, Veeraraghavan H, Oh JH, Jackson A, and Deasy JO. Library of deep-learning image segmentation and outcomes model-implementations. Physica Medica. 73:190-196, 2020.

[81] Do RKG, Reyngold M, Paudyal R, Oh JH, Konar AS, LoCastro E, Goodman K, and Shukla-Dave A. Diffusion weighted and dynamic contrast-enhanced MRI derived imaging metrics for stereotactic body radiotherapy of pancreatic ductal adenocarcinoma: Preliminary findings. Tomography. 6(2):261-271, 2020.

[80] Oh JH, Pouryahya M, Iyer A, Apte A, Deasy JO, and Tannenbaum A. A novel kernel Wasserstein distance on Gaussian measures: an application of identifying dental artifacts in head and neck computed tomography. Computers in Biology and Medicine. 120:103731, 2020.

[79] LoCastro E, Paudyal R, Mazaheri Y, Hatzoglou V, Oh JH, Lu Y, Konar AS, vom Eigen K, Ho A, Ewing JR, Lee N, Deasy JO, and Shukla-Dave A. Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer based on Dynamic Contrast Enhanced Magnetic Resonance Imaging: Feasibility Analysis. Tomography. 6(2):129-138, 2020.

[78] Lee S, Liang X, Woods M, Reiner AS, Concannon P, Bernstein L, Lynch CF, Boice JD, Deasy JO, Bernstein JL, and Oh JH. Machine Learning on Genome-Wide Association Studies to Predict the Risk of Radiation-Associated Contralateral Breast Cancer in the WECARE Study. PLoS One. 15(2):e0226157, 2020.

[77] Sanduleanu S, Jochems A, Upadhaya T, Even AJG,  Leijenaar RTH, Dankers FJWM, Klaassen R, Woodruff HC, Hatt M, Kaanders HJAM, Hamming-Vrieze O, van Laarhoven HWM, Subramiam RM, Huang SH, O'Sullivan B, Bratman SV, Dubois LJ,  Miclea RL, Di Perri D, Geets X, Crispin-Ortuzar M, Apte A, Deasy JO, Oh JH,  Lee NY, Humm JL, Schöder H, De Ruysscher D, Hoebers F, and Lambin P. Non-invasive imaging prediction of tumor hypoxia: a novel developed and externally validated CT and FDG-PET-based Radiomic Signature. Radiotherapy & Oncology. 153:97-105, 2020.

[76] Mallavarapu T, Hao J, Kim Y, Oh JH*, and Kang M*. Pathway-based Deep Clustering for Molecular Subtyping of Cancer. Methods. 173:24-31, 2020. [Co-senior author]

[75] Paudyal R, Lu Y, Hatzoglou V, Moreira A, Stambuk HE, Oh JH, Cunanan KM, Aramburu Nunez D, Mazaheri Y, Gonen M, Ho A, Fagin JA, Wong RJ, Shaha A, Tuttle RM, and Shukla-Dave A. Dynamic Contrast-Enhanced MRI Model Selection for Predicting Tumor Aggressiveness in Papillary Thyroid Cancers. NMR in Biomedicine. 33(1):e4166, 2019.

[74] Zarepisheha M, Hong L, Zhou Y, Oh JH, Mechalakos JG, Hunt MA, Mageras GS, and Deasy JO. Automated intensity modulated treatment planning: the expedited constrained hierarchical optimization (ECHO) system. Medical Physics. 46(7):2944-2954, 2019.

[73] Hao J, Kim Y, Mallavarapu T, Oh JH*, and Kang M*. Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data. BMC Medical Genomics. 12(Suppl 10):189, 2019. [Co-senior author]

[72] Aramburu Nunez D, Lu Y, Paudyal R, Hatzoglou V, Moreira AL, Oh JH, Stambuk HE, Mazaheri Y, Gonen M, Ghossein RA, Shaha AR, Tuttle RM, and Shukla-Dave A. Quantitative Non-Gaussian Intravoxel Incoherent Motion Diffusion Weighted Imaging Metrics and Surgical Pathology for Stratifying Tumor Aggressiveness in Papillary Thyroid Carcinomas. Tomography. 5:26-35, 2019.

[71] Thakur SB, Horvat JV, Hancu I, Sutton OM, Bernard-Davila B, Weber M, Oh JH, Leithner D, Brennan S, Giri D, Manderski E, Morris EA, and Pinker K. Quantitative In Vivo Proton MR Spectroscopic Assessment of Lipid Metabolism: Value for Breast Cancer Diagnosis and Prognosis. Journal of Magnetic Resonance Imaging. 50:239-249, 2019.

[70] Gay HA*, Oh JH*, Apte AP, Daly MD, Adkins DR, Rich J, Oppelt PJ, Dyk PT, Mullen DF, Eschen L, Chin RI, Nussenbaum B, Haughey BH, Thorstad WL, and Deasy JO. Predictors of Acute Throat or Esophageal Patient Reported Pain During Radiation Therapy for Head and Neck Cancer. Clinical and Translational Radiation Oncology. 13:1-6, 2018. [Co-first author]

[69] Hatzoglou V, Oh JH, Buck O, Lin X, Lee M, Shukla-Dave A, Young RJ, Peck K, Holodny AI, and Grommes C. Dynamic contrast-enhanced and diffusion-weighted MRI for prognosis of primary central nervous system lymphoma. Journal of Neuro-Oncology. 140(2): 351-358, 2018.

[68] Kang J, Rancati T, Lee S, Oh JH, Kerns S, Scott JG, Schwartz RS, Kim S, and Rosenstein BS. Machine learning and radiogenomics: lessons learned and future directions. Frontiers in Oncology. 8:228, 2018.

[67] Apte AP, Iyer A, Crispin-Ortuzar M, Pandya R, V.van Dijk L, Spezi E, Thor M, Um H, Veeraraghavan H, Oh JH, Shukla-Dave A, and Deasy JO. Technical Note: Extension of CERR for computational radiomics: a comprehensive MATLAB platform for reproducible radiomics research. Medical Physics. 45(8): 3713-3720, 2018.

[66] El Naqa I, Ruan D, Valdes G, Dekkre A, McNutt T, Ge Y, Wu J, Oh JH, Thor M, Smith W, Rao A, Fuller C, Xiao Y, Manion F, Schipper M, Mayo C, Moran J, and Ten Haken R. Machine Learning and Modeling: Data, Validation, Communication Challenges. Medical Physics. 45(10): e834-e840, 2018.

[65] Pouryahya M, Oh JH, Mathews J, Deasy JO, and Tannenbaum A. Characterizing cancer drug response and biological correlates: a geometric network approach. Scientific Reports. 8(1):6402, 2018.

[64] Crispin-Ortuzar M, Apte A, Grkovski, Oh JH, Lee NY, Schoder H, Humm JL, and Deasy JO. Predicting hypoxia status using a combination of contrast-enhanced computed tomography and [18F]-Fluorodeoxyglucose positron emission tomography radiomics features. Radiotherapy and Oncology. 127(1):36-42, 2018.

[63] Munck af Rosenschold P, Zelefsky MJ, Apte AP, Jackson A, Oh JH, Shulman E, Desai N, Hunt M, Ghadjar P, Yorke E, and Deasy JO. Image-guided radiotherapy reduces the risk of under-dosing high-risk prostate cancer extra-capsular disease and improves biochemical control. Radiation Oncology. 13(1):64, 2018.

[62] Lee S, Kerns S, Ostrer H, Rosenstein B, Deasy JO, and Oh JH. Machine Learning on a Genome-Wide Association Study to Predict Late Genitourinary Toxicity Following Prostate Radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 101:128-135, 2018.

[61] Dashevsky B, Oh JH, Apte A, Bernard-Davila B, Morris EA, Deasy JO, and Sutton EJ. MRI features predictive of negative surgical margins in patients with HER2 overexpressing breast cancer undergoing breast conservation. Scientific Reports. 8: 315, 2018.

[60] Choi W, Oh JH, Riyahi S, Liu CJ, Jiang F, Chen W, White C, Rimner A, Mechalakos JG, Deasy JO, and Lu W. Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer. Medical Physics. 45:1537-1549, 2018.

[59] Dean J, Wong K, Gay H, Welsh L, Jones A-B, Schick U, Oh JH, Apte A, Newbold K, Bhide S, Harrington K, Deasy JO, Nutting C, and Gulliford S. Incorporating spatial dose metrics in machine learning-based normal tissue complication probability (NTCP) models of severe acute dysphagia resulting from head and neck radiotherapy. Clinical and Translational Radiation Oncology. 8:27-39, 2018.

[58] Taunk NK, Oh JH, Shukla-Dave A, Beal K, Vachha B, Holodny A, and Hatzoglou V. Early post-treatment assessment of MRI perfusion biomarkers can predict long-term response of lung cancer brain metastases to stereotactic radiosurgery. Neuro Oncology. 20:567-575, 2018.

[57] Thor M, Olsson CE, Oh JH, Hedstrom J, Pauli N, Johansson M, Deasy JO, and Finizia C. Temporal patterns of patient-reported trismus and associated mouth-opening distances in radiotherapy for head and neck cancer: A prospective cohort study. Clinical Otolaryngology. 43:22-30, 2018.

[56] Jeong J, Oh JH, Sonke J-J, Belderbos J, Bradley JD, Fontanella AN, Rao SS, and Deasy JO. Modeling the cellular response of lung cancer to radiation therapy for a broad range of fractionation schedules. Clinical Cancer Research. 23(18): 5469-5479, 2017.

[55] Folkert MR, Setton J, Apte AP, Grkovski M, Young RJ, Schoder h, Thorstad WL, Lee NY, Deasy JO, and Oh JH. Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics. Physics in Medicine and Biology. 62(13): 5327-5343, 2017.

[54] Zarayeneh N, Suh S, Oh JH, Liu C, Gao J, Ko E, Kim E, and Kang M. Integration of multi-omics data for integrative gene regulatory network inference. International Journal  of Data Mining and Bioinformatics. 18(3): 223-239, 2017.

[53] Pommer T, Oh JH, Munck af Rosenschold P, and Deasy JO. Simulating intrafraction prostate motion with a random walk model. Advances in Radiation Oncology. 2(3): 429-436, 2017.

[52] Steineck G, Skokic V, Sjoberg F, Bull C, Alevronta E, Dunberger G, Bergmark K, Wilderang U, Oh JH, Deasy JO, and Jornsten R. Identifying radiation-induced survivorship syndromes affecting bowel health in a cohort of gynecological cancer survivors. PLoS One. 12(2):e0171461, 2017.

[5`] Oh JH, Kerns S, Ostrer H, Powell SN, Rosenstein B, and Deasy JO. Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes. Scientific Reports, 7: 43381, 2017.

[50] Owosho AA, Thor M, Rosenberg H, Yom SK, Oh JH, Riaz N, Tsai CJ, Deasy JO, Lee N,  Huryn JM, and Estilo CL. The role of parotid gland irradiation in the development of severe hyposalivation (xerostomia) after intensity-modulated radiation therapy for head and neck cancer: Temporal patterns, risk factors, and testing the QUANTEC guidelines. Journal of Cranio-Maxillofacial Surgery. 45(4): 595-600, 2017.

[49] Huang EX, Robinson CG, Molotievschi A, Bradley JD, Deasy JO, and Oh JH. Independent test of a model to predictive severe acute esophagitis. Advances in Radiation Oncology. 2(1): 37-43, 2017.

[48] Paudyal R, Oh JH, Riaz N, Venigalla P, Li J, Hatzoglou V, Leeman J, Nunez DA, Lu Y, Deasy JO, Lee N, and Shukla-Dave A. Intravoxel incoherent motion diffusion-weighted MRI during chemoradiation therapy to characterize and monitor treatment response in human papillomavirus head and neck squamous cell carcinoma. Journal of Magnetic Resonance Imaging. 45(4): 1013-1023, 2017.

[47] Tyagi N, Sutton E, Hunt M, Zhang J, Oh JH, Apte A, Mechalakos J, Wilgucki M, Gelb E, Mehrara B, Matros E, and Ho A. Morphologic Features of Magnetic Resonance Imaging as a Surrogate of Capsular Contracture in Breast Cancer Patients With Implant-based Reconstructions. International Journal of Radiation Oncology*Biology*Physics. 97(2): 411-419, 2017.

[46] Thor M, Owosho AA, Clark HD, Oh JH, Riaz N, Hovan A, Tsai J, Thomas SD, Yom SH, Wu JS, Huryn JM, Moiseenko V, Lee NY, Estilo CL, and Deasy JO. Internal and external generalizability of temporal dose-response relationships for xerostomia following IMRT for head and neck cancer. Radiotherapy and oncology. 122(2): 200-206, 2017.

[45] Dean JA, Wong KH, Gay H, Welsh LC, Jones AB, Schick U, Oh JH, Apte A, Newbold KL, Bhide SA, Harrington KJ, Deasy JO, Nutting CM, and Gulliford SL. Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 96(4): 820-831, 2016.

[44] Oh JH, Thor M, Olsson C, Skokic V, Jörnsten R, Alsadius D, Pettersson N, Steineck G, and Deasy JO. A factor analysis approach to investigate the relationship between radiation dose and side effects after radiotherapy from patient reported outcomes. Methods of Information in Medicine, 55(5):431-439, 2016.       

[43] Hatzoglou V, Omuro AM, Haque S, Khakoo Y, Ganly I, Oh JH, Shukla-Dave A, Fatovic R, Gaal J, and Holodny AI. Second-opinion interpretations of neuroimaging studies by oncologic neuroradiologists can help reduce errors in cancer care. Cancer, 122(17):2708-2714, 2016.

[42] Thor M, Olsson C, Oh JH, Petersen SE, Alsadius D, Høyer M, Pettersson N, Bentzen L, Deasy JO, Muren LP, and Steineck G. Urinary bladder dose-response relationships for patient-reported genitourinary morbidity domains following prostate cancer radiotherapy. Radiotherapy and oncology. 119(1): 117-122, 2016.

[41] de la Fuente M, Young R, Rubel J, Rosenblum MK, Tisnado J, Briggs S, Cross J, Campos C, Straley K, Zhu D, Dong C, Thomas A, Omuro A, Nolan C, Pentsova E, Kaley T, Oh JH, Noeske R, Maher E, Choi C, Gutin P, Holodny A, Yen K, DeAngelis L, Mellinghoff I, and Thakur S. Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma. Neuro-Oncology. 18:283-290, 2016.

[40] Oh JH and Deasy JO. A literature mining-based approach for identification of cellular pathways associated with chemoresistance in cancer. Briefings in Bioinformatics. 17(3): 468-478, 2016.

[39] Michalak K, Maciak S, Kim YB, Santopietro G, Oh JH, Kang L, Garner HR, and Michalak P. Nucleolar dominance and maternal control of 45S rDNA expression. Proceedings of the Royal Society B. 282: 20152201, 2015.

[38] Thor M, Olsson C, Oh JH, Alsadius D, Pettersson N, Deasy JO, and Steineck G. Radiation dose to the penile structures and patient-reported sexual dysfunction in long-term prostate cancer survivors. Journal of Sexual Medicine. 12:2388-2397, 2015.

[37] Sutton EJ, Dashevsky B, Oh JH, Veeraraghavan H, Apte AP, Thakur SB, Morris EA, and Deasy JO. Breast cancer molecular subtype classifier that incorporates MRI texture features. Journal of Magnetic Resonance Imaging. 44: 122-129, 2016.

[36] Son CH, Law E, Oh JH, Apte AP, Yang TJ, Riedel E, Wu AJ, Deasy JO, and Goodman KA. Dosimetric predictors of radiation-induced vaginal stenosis after pelvic radiation therapy for rectal and anal cancer. International Journal of Radiation Oncology*Biology*Physics. 92(3): 548-554, 2015.

[35] Thor M, Olsson CE, Oh JH, Petersen SE, Alsadius D, Bentzen L, Pettersson N, Muren LP, Waldenström AC, Høyer M, Steineck G, and Deasy JO. Relationships between dose to the gastro-intestinal tract and patient-reported symptom domains after radiotherapy for localized prostate cancer. Acta Oncologica. 54(9): 1326-1334, 2015.

[34] Kerns SL, Kundu S, Oh JH, Singhal SK, Janelsins M, Travis LB, Deasy JO, Janssens AC, Ostrer H, Parliament M, Usmani N, and Rosenstein BS. The prediction of radiotherapy toxicity using single nucleotide polymorphism (SNP)-based models: a step towards prevention. Seminars in Radiation Oncology. 25(4): 281-291, 2015.

[33] Sutton EJ, Oh JH, Dashevsky BZ, Veeraraghavan H, Apte AP, Thakur SB, Deasy JO, Morris EA. Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay. Journal of Magnetic Resonance Imaging. 42(5): 1398-1406, 2015.

[32] Julie DAR, Oh JH, Apte A, Deasy JO, Tom A, Wu AJ, and Goodman KA. Predictors of acute toxicities during definitive chemoradiation using intensity modulated radiotherapy for anal squamous cell carcinoma. Acta Oncologica. 55:208-216, 2016.

[31] Cella L, Oh JH, Palma G, Deasy JO, Liuzzi R, D'Avino V, Conson M, Picardi M, Salvatore M, and Pacelli R. Predicting radiation-induced valvular heart damage. Acta Oncologica. 54(10): 1796-1804, 2015.

[30] Folkert MR, Bilsky MH, Cohen GN, Voros L, Oh JH, Zaider M, Laufer I, and Yamada Y. Local recurrence outcomes using the 32P intraoperative brachytherapy plaque in the management of malignant lesions of the spine involving the dura. Brachytherapy. 14(2): 202-208, 2015.

[29] Cella L, Palma G, Deasy JO, Oh JH, Liuzzi R, D'Avino V, Conson M, Pugliese N, Marco P, Marco S, and Pacelli R. Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role? PLoS ONE. 9(10):e111753, 2014.

[28] Yang TJ, Oh JH, Apte A, Son CH, Deasy JO, and Goodman KA. Clinical and Dosimetric Predictors of Acute Hematologic Toxicity in Rectal Cancer Patients Undergoing chemoradiotherapy. Radiotherapy and oncology. 113, 29-34, 2014.

[27] Kim YB, Oh JH, McIver LJ, Rashkovetsky E, Michalak K, Garner HR, Kang L, Nevo E, Korol AB, and Michalak P. Divergence of drosophila melanogaster repeatomes in response to a sharp microclimate contrast in evolution canyon, Israel. Proc Natl Acad Sci U S A. 111(29), 10630-11635, 2014.

[26] Yang TJ, Oh JH, Folkert MR, Gupta G, Shi W, Zhang Z, Morikawa A, Seidman A, Brennan C, Yamada Y, Chan TA, and Beal K. Outcomes and prognostic factors of women with 1-3 breast cancer brain metastases treated with definitive stereotactic radiosurgery. Journal of Radiation Oncology*Biology*Physics. 90(3), 518-525, 2014.

[25] Jeong J, Setton JS, Lee NY, Oh JH, and Deasy JO. Estimate of the impact of FDG-avidity on the dose required for head and neck radiotherapy local control. Radiotherapy and Oncology. 111(3), 340-347, 2014.

[24] Rao S, Oh JH, Jackson A, and Deasy JO. In response to Brown et al.:  does one (linear-quadratic) size really fit all? Journal of Radiation Oncology*Biology*Physics. 89(3): 692-693, 2014.

[23] Oh JH and Deasy JO. Inference of radio-responsive gene regulatory networks using the graphical lasso algorithm. BMC Bioinformatics. 15(Suppl 7):S5, 2014.

[22] Folkert MR, Bilsky MH, Tom AK, Oh JH, Alektiar KM, Laufer I, Tap WD, and Yamada Y. Outcomes and Toxicity for Hypofractionated and Single-Fraction Image-Guided Stereotactic Radiosurgery for Sarcomas Metastasizing to the Spine. International Journal of Radiation Oncology*Biology*Physics. 88(5): 1085-1091, 2014.

[21] Munch af Rosenschöld PM, Desai NB, Oh JH, Apte A, Hunt M, Kalikstein A, Mechalakos J, Happersett L, Deasy JO, and Zelefsky MJ. Modeling positioning uncertainties of prostate cancer external beam radiation therapy using pre-treatment data. Radiotherapy and oncology. 110(2):251-255, 2014.

[20] Sveistrup J, Af Rosenschöld PM, Deasy JO, Oh JH, Pommer T, Petersen PM, and Engelholm SA. Improvement in toxicity in high risk prostate cancer patients treated with image-guided intensity-modulated radiotherapy compared to 3D conformal radiotherapy without daily image guidance. Radiation Oncology. 9(1):44, 2014.

[19] Ghadjar P, Zelefsky MJ, Spratt D, Munck af Rosenschöld P, Oh JH, Hunt M, Kollmeier M, Happersett L, Yorke E, Deasy JO, and Jackson A. The impact of dose to the bladder trigone on long-term urinary function after high-dose intensity-modulated radiation therapy for localized prostate cancer. International Journal of Radiation Oncology*Biology*Physics. 88:339-344, 2014.

[18] Oh JH and Deasy JO. SITDEM: A simulation tool for disease/endpoint models of association studies based on single nucleotide polymorphism genotypes. Computers in Biology and Medicine. 45:136-142, 2014.

[17] Hübner S, Rashkovetsky E, Kim YB, Oh JH, Michalak K, Weiner D, Korol AB, Nevo E, and Michalak P. Genome differentiation of Drosophila melanogaster from a microclimate contrast in Evolution Canyon, Israel. Proc Natl Acad Sci U S A. 110(52):21059-21064, 2013.

[16] Yang TJ, Oh JH, Son CH, Apte A, Deasy JO, Wu A, and Goodman KA. Predictors of acute gastrointestinal toxicity during pelvic radiotherapy in patients with rectal cancer. Gastrointestinal Cancer Research. 6:129-136, 2013.

[15] Ghadjar P, Jackson A, Spratt DE, Oh JH, Munck af Rosenschöld P, Kollmeier M, Yorke E, Hunt M, Deasy JO, and Zelefsky MJ. Patterns and predictors of amelioration of genitourinary toxicity after high-dose intensity-modulated radiation therapy for localized prostate cancer: implications for defining postradiotherapy urinary toxicity. European Urology. 64(6):931-938, 2013.

[14] Oh JH, Wong HP, Wang X, and Deasy JO. A bioinformatics filtering strategy for identifying radiation response biomarker candidates. PLoS ONE. 7(6):e38870, 2012.

[13] Oh JH, Craft JM, Townsend RR, Deasy JO, Bradley JD, and El Naqa I. A Bioinformatics approach for biomarker identification in radiation-induced lung inflammation from limited proteomics data. Journal of Proteome Research. 10:1406-1415, 2011.

[12] Oh JH, Craft JM, Al-Lozi R, Vaidya M, Meng Y, Deasy JO, Bradley JD, and El Naqa I. A Bayesian network approach for modeling local failure in lung cancer. Physics in Medicine and Biology. 56:1635-1651, 2011.

[11] Oh JH, Yang Y, and El Naqa I. Adaptive learning for relevance feedback: application to digital mammography. Medical Physics. 37:4432-4444, 2010.

[10] Oh JH and Gao J. Fast kernel discriminant analysis for classification of liver cancer mass spectra.  IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8:1522-1534, 2011.

[9] Oh JH, Pan S, Zhang J, and Gao J. MSQ: a tool for quantification of proteomics data generated by a liquid chromatography/matrix-assisted laser desorption/ ionization time-of-flight tandem mass spectrometry based targeted quantitative proteomics platform. Rapid Communications in Mass Spectrometry. 24:403-408, 2010.

[8] Oh JH, Apte A, Al-Lozi R, Bradley J, and El Naqa I. Towards prediction of radiation pneumonitis arising from lung cancer patients using machine learning approaches. Journal of Radiation Oncology Informatics. 1:30-43, 2009.

[7] Oh JH, Lotan Y, Gurnani P, Rosenblatt KP, and Gao J. Prostate cancer biomarker discovery using high performance mass spectral serum profiling. Computer Methods and Programs in Biomedicine. 96:33-41, 2009.

[6] Oh JH, Gurnani P, Schorge J, Rosenblatt KP, and Gao J. An extended Markov blanket approach to proteomic biomarker detection from high-resolution mass spectrometry data. IEEE Transactions on Information Technology in Biomedicine. 13:195-206, 2009.

[5] Oh JH and Gao J. A kernel-based approach for detecting outliers of high-dimensional biological data. BMC Bioinformatics. 10:S7, 2009.

[4] Oh JH, Kim YB, Gurnani P, Rosenblatt KP, and Gao J. Biomarker selection and sample prediction for multi-category disease on MALDI-TOF data. Bioinformatics. 24:1812-1818, 2008.

[3] Pan S, Rush J, Peskind ER, Galasko D, Chung K, Quinn J, Jankovic J, Leverenz JB, Zabetian C, Pan C, Wang Y, Oh JH, Gao J, Zhang J, Montine T, and Zhang J. Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform. Journal of Proteome Research. 7:720-730, 2008.

[2] Oh JH, Nandi A, Gurnani P, Knowles L, Schorge J, Rosenblatt KP, and Gao J. Proteomic biomarker identification for diagnosis of early relapse in ovarian cancer. Journal of Bioinformatics and Computational Biology. 4:1159-1179, 2006.

[1] Oh JH and Gao J. A two-way parallel searching algorithm for peptide identification via tandem mass spectrometry. Special Issue on Bioinformatics, Engineering Letters. 13:344-354, 2006.

Book chapters

[5] Oh JH, Lee S, Thor M, and Deasy JO. Using AI to Predict Radiotherapy Toxicity Risk Based on Patient Germline Genotyping. Artificial Intelligence in Radiation Oncology, World Scientific Publishing, 2022.

[4] Deasy JO, Apte A, Thor M, Jeong J, Iyer A, Oh JH, and Jackson A. Radiotherapy Outcomes Modeling in the Big Data Era. Big Data in Radiation Oncology, CRC Press. Chapter 15, 2019.

[3] Rosenstein BS, Pandey G, Speers C, Oh JH, West C, and Mayo C. Radiogenomics.  Big Data in Radiation Oncology, CRC press. Chapter 13, 2019.

[2] El Naqa I, Oh JH, and Yang Y. Relevance feedback as new tool for computer-aided diagnosis in image databases. Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, IGI Global. 86-106, 2012.

[1] El Naqa I, Craft JM, Oh JH, and Deasy JO. Biomarkers for early radiation response for adaptive radiation therapy. Adaptive Radiation Therapy, CRC Press. 53-67, 2011.

Peer-reviewed conference/workshop papers

[27] Oh JH, Apte A, Veeraraghavan H, Shukla-Dave A, and Deasy JO. Prediction of survival outcomes and relevant tumor immune infiltrates using radiomic network analysis. International Conference on the use of Computers in Radiation therapy (ICCR), Lyon, France, 2024.

[26] Apte AP, Iyer A, LoCastro E, Elguindi S, Jiang J, Oh JH, Veeraraghavan H, Shukla-Dave A, and Deasy JO. pyCERR - A Python-based Computational Environment for Radiological Research. International Conference on the use of Computers in Radiation therapy (ICCR), Lyon, France, 2024.

[25] Oh JH, Elkin R, Simhal A, Zhu J, Deasy JO, and Tannenbaum A. Optimal Transport for Kernel Gaussian Mixture Models. NeurIPS Workshop on Optimization for Machine Learning, 2023.

[24] Hao J, Masum M, Oh JH, and Kang M. Gene- and Pathway-based Deep Neural Network for Multi-omics Data Integration to Predict Cancer Survival Outcomes. International Symposium on Bioinformatics Research and Applications (ISBRA). Barcelona, Spain, 113-124, 2019.

[23] Mallavarapu T, Hao J, Kim Y, Oh JH, and Kang M. PASCL: Pathway-based Sparse Deep Clustering for Identifying Unknown Cancer Subtypes. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 470-475, 2018.

[22] Hao J, Kim Y, Mallavarapu T, Oh JH, and Kang M. Cox-PASNet: Pathway-based Sparse Deep Neural Network for Survival Analysis. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 381-386, 2018.

[21] Mallavarapu T, Kim Y, Oh JH, and Kang M. R-PathCluster: Identifying cancer subtype of glioblastoma multiforme using pathway-based restricted boltzmann machine. International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics, 1183-1188, 2017.

[20] Zarayeneh N, Oh JH, Kim D, Liu C, Gao J, Suh SC, and Kang M. Integrative gene regulatory network inference using multi-omics data. 9th International Workshop on Biological Network Analysis and Integrative Graph-Based Approaches (IWBNA), 1336-1340, 2016.

[19] Chen J*, Oh JH*, Sandhu R, Lee S, Deasy JO, and Tannenbaum A. Transcriptional responses to ultraviolet and ionizing radiation: an approach based on graph curvature. 9th International Workshop on Biological Network Analysis and Integrative Graph-Based Approaches (IWBNA), 1302-1306, 2016.

[18] Oh JH, Craft JM, Al-Lozi R, Vaidya M, Meng Y, Deasy JO, Bradley JD, and El Naqa I. Predicting local failure in lung cancer using Bayesian networks. Proceedings of IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Special Session on Machine Learning Methods for Modeling Treatment Outcomes in Cancer and Radiation Therapy, 735-739, 2010.

[17] Oh JH, Apte A, El Naqa I, and Deasy JO. Tools for extracting and analyzing dose-volume-outcomes relationships: improvements to the dose response explorer system (DREES). International Conference on the Use of Computers in Radiation Therapy, 2010.

[16] Oh JH, Al-Lozi R, and El Naqa I. Application of machine learning techniques for prediction of radiation pneumonitis in lung cancer patients. Proceedings of IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Special Session on Machine Learning Methods for Modeling Treatment Outcomes in Cancer and Radiation Therapy, 478-483, 2009.

[15] Oh JH and El Naqa I. Bayesian network learning for detecting reliable interactions of dose-volume related parameters in radiation pneumonitis. Proceedings of IEEE International Conference on Machine Learning and Applications (IEEE ICMLA), Special Session on Machine Learning Methods for Modeling Treatment Outcomes in Cancer and Radiation Therapy, 484-488, 2009.

[14] Oh JH, El Naqa I, and Yang Y. Online learning of relevance feedback from expert readers for mammogram retrieval. Proceedings of IEEE Asilomar Conference on Signals, Systems and Computers, 17-21, 2009.

[13] Oh JH, Gao J, and Rosenblatt KP. Biological data outlier detection based on Kullback-Leibler divergence. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 249-254, 2008.

[12] Peswani DL, Mathker A, Kashyap D, Bensalah K, Tuncel A, Kabbani W, Cadeddu J, Oh JH, Gao J, and Liu H. Feasibility of detecting prostate adenocarcinoma using optical reflectance spectroscopy. In Biomedical Optics, Technical Digest (CD), Optical Society of America, BTuF44, 2008.

[11] Oh JH, Kim YB, Gurnani P, Rosenblatt KP, and Gao J. A novel classification method for analysis of multi-stage diseases via mass spectrometric data. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 237-242, 2007.

[10] Oh JH, Kim YB, Gao J, Nandi A, Gurnani P, and Rosenblatt KP. Biomarker selection in Alzheimer disease using high-resolution MALDI-TOF data. Proceedings of IEEE Symposium on Bioinformatics and Bioengineering (IEEE BIBE), 464-471, 2007.

[9] Kim YB, Oh JH, and Gao J. Improvement of performance in multiclass problems by using biclassification based on error-correcting output code. Proceedings Conference on Machine Learning and Data Analysis (ICMLDA), 677-682, 2007.

[8] Kim YB, Oh JH, and Gao J. Error-correcting output code based on feature selection in multiclass learning problems. Second IAPR International Workshop on Pattern Recognition in Bioinformatics (PRIB), 2007.

[7] Oh JH, Nandi A, Gurnani P, Bryant-Greenwood P, Rosenblatt KP, and Gao J. Prediction of labor for pregnant women using high-resolution mass spectrometry data. Proceedings of IEEE Symposium on Bioinformatics and Bioengineering (IEEE BIBE), 332-339, 2006.

[6] Oh JH, Nandi A, Gurnani P, Knowles L, Schorge J, Rosenblatt KP, and Gao J. Classification of relapse ovarian cancer on MALDI-TOF mass spectrometry data. Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), 36-43, 2006.

[5] Oh JH, Gao J, Nandi A, Gurnani P, Knowles L, Schorge J, and Rosenblatt KP. Diagnosis of early relapse in ovarian cancer using serum proteomic profiling. Genome Informatics Workshop (GIW). Genome Informatics, 16:195-204, 2005.

[4] Oh JH, Gao J, Nandi A, Gurnani P, Knowles L, Schorge J, and Rosenblatt KP. Multicategory classification using extended SVM-RFE and Markov blanket on SELDI-TOF mass Spectrometry data. Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), 339-345, 2005.

[3] Oh JH and Gao J. Peptide identification by tandem mass spectra: an efficient parallel searching. Proceedings of IEEE Symposium on Bioinformatics and Bioengineering (IEEE BIBE), 161-168, 2005.

[2] Kim YB, Oh JH, and Gao J. Emerging pattern based subspace clustering of microarray gene expression using mixture models. Proceedings of International Conference on Bioinformatics and its Applications (ICBA), 13-24, 2004.

[1] Oh JH, Kim YB, and Gao J. A two-way searching algorithm for de novo peptide sequencing via tandem mass spectrometry. Proceedings of International Conference on Bioinformatics and its Applications (ICBA), 402-413, 2004.

Abstracts

[179] Grange D, Iyer A, Ebrahimpour L, Chen X, Jiang J, Bale TA, Masoumi E, Apte AP, Calderon F, Xing S, Swinburne N, Young R, Peck KK, Oh JH, Moss NS, and Deasy JO. Optimal transport modeling of DCE-MRI to distinguish radiation necrosis from tumor reveals fluid-flow phenotypes in brain metastases. SPIE Medical Imaging. Vancouver, Canada, 2027.

[178] Kocher CD, Simhal AK, Ebrahimpour L, Oh JH, Srivastava H, Grange D, Norton L, and Deasy JO, and Weistuch C. A minimal machine learning model for predicting biochemical treatment response in metastatic breast cancer. SABCS, San Antonio, TX, 2026. 

[177] Srivastava H, Oh JH, Ebrahimpour L, Kocher C, Weistuch C, Pareja F, Norton L, Boehm K, and Deasy JO. Virchow2-Based Segmentation Identifies Prognostic Spatial Features in Triple-Negative Breast Cancer. SABCS, San Antonio, TX, 2026. 

[176] Elkin R, Oh JH, Srivastava H, Djerroudi L, Norton L, Deasy JO, and Pareja F. Relational Modeling of Continuous Invasive Lobular Carcinoma Biology Reveals Clinically Relevant Disease States. SABCS, San Antonio, TX, 2026.

[175] Ebrahimpour L, Sutton E, Srivastava H, Nayak L, Oh JH, Apte A, LoCastro E, Norton L, Veeraraghavan H, Jiang J, and Deasy JO. Evaluation and failure analysis of a foundation model for automated breast tumor segmentation on post-contrast breast MRI. SABCS, San Antonio, TX, 2026. 

[174] Ebrahimpour L, Oh JH, Srivastava H, Elkin R, Kocher C, Weistuch C, Norton L, and Deasy JO. Evaluating MRI radiomics-derived clusters and feature-level associations with computational pathology in TCGA-BRCA. SABCS, San Antonio, TX, 2026.

[173] Grange D, Chen X, Elkin R, Iyer A, Apte A, Moss N, Swinburne N, Peck K, Oh JH, and Deasy JO. Optimal mass transport time-derivative features help distinguish radiation necrosis from tumor recurrence. RSNA, Chicago, IL, 2026.

[172] Srivastava H, Oh JH, Seyed Ebrahimpour L, Norton L, Bohm K, and Deasy JO. ViP-SegD: Virchow2-based Pixel-wise Segmentation of the Tumor Microenvironment in Breast and Lung Whole-slide Images, ISMB, Washington DC, 2026. 

[171]  Wei W, Elkin R, Deasy JO, and Oh JH. Network-based optimal transport analysis of gut microbiome data in colorectal cancer. CAMDA 2026, Washington DC, 2026.

[170] Elkin R, Askarifirouzjaei H, Oh JH, Han D, Qi H, Vermeulen M, Fan S, Lin H, Simone CB II, Baltaci M, Russell J, Powell SN, Humm J, Haimovitz-Friedman A and Deasy JO. Single-cell network curvature distinguishes radiation modality and drug-combination responses. Radiation Research Society, Hawaii, 2026.

[169] Askarifirouzjaei H, Oh JH, Elkin R, Han D, Vermeulen M, Fan S, Lin H, Simone CB II, Baltaci M, Russell J, Powell SN, Humm J, Haimovitz-Friedman A, and Deasy JO. Spironolactone causes proton-specific synthetic lethality via XPB-dependent repair disruption. Radiation Research Society, Hawaii, 2026. 

[168] Askarifirouzjaei H, Oh JH, Elkin R, Han D, Qi H, Vermeulen M, Lin H, Simone CB II, Baltaci M, Russell J, Powell SN, Humm J, Haimovitz-Friedman A, and Deasy JO. Distinct coexpression architectures after proton and photon irradiation reveal a photon-associated metabolic pseudohypoxia program. Radiation Research Society, Hawaii, 2026.

[167] Liu X, Oh JH, Zhang YH, Cervino LA, Zhang P, Gelblum D, Shaverdian N, Iyengar P, Simone CB, Wu AJ, Rimner A, Gomez D, Shepherd AF, and Ma J. Correlation Between Tumor Volume, Symptom Relief, and Survival in Metastatic NSCLC Patients Treated Prospectively with Cyclical "Quad Shot" Radiotherapy. World Conference on Lung Cancer, Seoul, South Korea, 2026.

[166] Apte AP, LoCastro E, Oh JH, Gregucci F, Pennell R, Yoffe L, Kim J, Chang Y, Elkin R, Chetrit NB, Montagna C, Shiao SL, Cheung K, Golden E, Weichselbaum RR, Formenti S, and Deasy JO. Findable, Accessible, Interoperable, Reusable, and Rerunnable (FAIReR) Informatics for ROBIN- ImmunoRad. ASTRO, Boston, MA, 2026.

[165] Askarifirouzjaei H, Oh JH, Elkin R, Han D, Hang Qi3, Vermeulen M, Lin H, Hasan S, Simone CB, Baltaci M, Powell SN, Haimovitz-Friedman A, and Deasy JO. Spironolactone drives synthetic lethality with proton irradiation but not photon irradiation through persistent transcription–replication conflicts and checkpoint state collapse. ASTRO, Boston, MA, 2026.

[164] Oh JH, Apte A, Auer P, Hall W, Deasy JO, and Kerns S. Multicohort Validation of Genetic Variants Associated with Radiation-Induced Hematuria in Prostate Cancer Patients. ASTRO, Boston, MA, 2026.

[163] George B, Jin C, Auer P, Xialong M, Marples B, Oh JH, Hall W, and Kerns S. Effect of Pelvic Radiation on Systemic Gene Expression Changes in a Prospective Study of Non-Metastatic Prostate Cancer. ASTRO, Boston, MA, 2026.

[162] Srivastava H, Oh JH, Ebrahimpour L, Mathew JC, Norton L, Boehm K, and Deasy JO. Immune infiltration features relative to cancer cell clumps predicts survival in triple negative breast cancer. ASCO, Chicago, Illinoi, 2026.

[161] Oh JH, Zhu Y, Srivastava H, Ebrahimpour L, Elkin R, Kocher C, Weistuch C, Norton L, Riaz N, and Deasy JO. PSG copy number amplification is associated with poor survival in early-stage female lung adenocarcinoma patients. ASCO, Chicago, Illinoi, 2026.

[160] Awais M, Aliotta E, Oh JH, Paudyal R, Apte A, Grkovski M, Diplas BH, Han J, Hatzoglou V, Schoder H, Riaz N, Lee N, and Shukla-Dave A.  Multimodal AI-based Analysis for Predicting Tumor Hypoxia and Treatment Response in Oropharyngeal Cancer. ISMRM Cancer Workshop, Madrid, Spain, 2026.

[159] Paudyal R, Oh JH, Diplas BH, Han JE, Miller DG, Hatzoglou V, Riaz  N, Lee N, and Shukla-Dave A. DKI for Evaluating Microstructural Changes in HPV-related Oropharyngeal Cancer Undergoing Radiation Therapy. ISMRM Cancer Workshop, Madrid, Spain, 2026. 

[158] Shukla-Dave A, Paudyal R, Diplas BH, Oh JH, Brown DN, Hatzoglou V, Weigelt B, Lee N, and Riaz N. DKI Biomarkers and ctDNA Kinetics: Tissue  Microstructure and Molecular Signatures for Evaluating Cancer. ISMRM Cancer Workshop, Madrid, Spain, 2026.

[157] Oh JH, Zhu Y, Srivastava H, Ebrahimpour L, Elkin R, Norton L, Riaz N, and Deasy JO.Copy number amplification of PSG is associated with poor survival in female lung adenocarcinoma patients. AACR, San Diego, California, USA, 2026.

[156] Elkin R, Oh JH, Simhal AK, and Deasy JO. Multi-modal integration in the NetFlow framework for comprehensive exploratory data analysis. AACR, San Diego, California, USA, 2026.

[155] Oh JH, Talbot CJ, Seibold P, Auer P, Hall W, Deasy JO, and Kerns S. Genetically Informed Biological Pathway Analysis of Late Hematuria Risk Following Prostate Radiotherapy. ESTRO, Stockholm, Sweden, 2026.

[154] Oh JH, Rizzuto G, Elkin R, Weistuch C, Norton L, Dveksler G, and Deasy JO. Pregnancy-specific glycoproteins in tumors are strong predictors of outcome in female lung adenocarcinoma patients. AACR, Chicago, IL, 2026.

EurekAlert! https://www.eurekalert.org/multimedia/1071189

[153] Dopeso H, Ferrando L, Gusain L, Farahani SJ, Shen S, Mamtani A, Schwartz C, Joergensen G, Repetto M, Gazzo A, Oh JH, Razavi P, Chandarlapaty S, Ross DS, Wen H, Brogi E, Zhang H, Lee AV, Oesterreich S, Weigelt B, and Pareja F. Deciphering Molecular Mechanisms RHOA-Altered Lobular Breast Cancer. ESMO, Berlin, Germany, 2025.

[152] Apte A, LoCastro E Iyer A, Elguindi S, Jiang J, Oh JH, Veeraraghavan H, Shukla-Dave A, and Deasy JO. Artificial Intelligence Apps for Medical Image Analysis using pyCERR and Cancer Genomics Cloud. AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning, Montreal, Canada, 2025.

[151] Simhal AK, Elkin R, Firestone RS, Oh JH, and Deasy JO. Variational Autoencoder Analysis Reveals Hidden Multiple Myeloma Subtypes. AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning, Montreal, Canada, 2025.

[150] Oh JH, Pareja F, Elkin R, Norton L, and Deasy JO. Identifying triple-negative breast cancer patients at high risk of worse prognosis using molecular features derived from histology images. AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning, Montreal, Canada, 2025.

[149] Treechairusame T, Zhang P, Hu YC, Aliotta E, Li A, Aristophanous M, Cervino, Deasy JO, Lee N, Zhang P, and Oh JH. Early salivary gland shrinkage is associated with an increased risk of acute xerostomia in head and neck cancer patients following radiotherapy. ASTRO, San Francisco, CA, 2025.

[148] Firestone R, Simhal A, Akhlaghi T, Oh JH, Maclachlan K, Garces JJ, Mailankody S, Hassoun H, Shah UA, Korde N, Tan CR, Rajeeve S, Hashmi H, Lesokhin AM, Deasy JO, Usmani SZ, and Hultcrantz M. Immune profiling identifies a functionally high-risk smoldering multiple myeloma patient population. ASCO, Chicago, IL, 2025.

[147] Singh A, Treechairusame T, Dee EC, Oh JH, Zhang P, Xiong J, Wu Y, Kang JJ, Tsai J, Gelblum DY, Yu Y, McBride SM, Riaz N, Zakeri K, Chen L, Shamseddine A, Huryn J, Wong RJ, Estilo C, and Lee NY. Prevalence And Predictors of Osteoradionecrosis of the jaw Following Post-Operative Intensity-Modulated Radiation Therapy and Proton Therapy for Oral Cavity Cancer. ASCO, Chicago, IL, 2025.

[146] Apte AP, LoCastro EM, Iyer A, Elguindi S, Jiang J, Oh JH, Veeraraghavan H, Shukla-Dave A, and Deasy JO. Python-Native Cerr for Cloud-Based Medical Image Analyses. AAPM, Washington DC, 2025.

[145] LoCastro EM, Iyer A, Oh JH, Jiang J, Veeraraghavan H, Elguindi SF, Shukla-Dave A, Deasy JO, and Apte AP. Cloud Workflow AI apps for radiotherapy image analysis using pyCERR and Seven Bridges-Cancer Genomics Cloud. AAPM, Washington DC, 2025.

[144] Treechairusame T, Zhang P, Hu Y, Oh JH, Li A, Aristophanous M, Cervino L, Lee N, and Zhang P. Assessing weekly parotid gland shrinkage and predicting acute xerostomia via an automated watchdog in adaptive radiotherapy environment of head and neck cancer. AAPM, Washington DC, 2025.

[143] Treechairusame T, Singh A, Dee EC, Oh JH, Zhang P, Xiong J, Aliotta E, Safavi AH, Wu Y, Caineng C, Gelblum DY, Sherman EJ, Huryn JM, SK Yom, Ganly I, Cracchiolo JR, Cohen MA, Wong RJ, Estilo CL, and Lee NY. Predictors of Osteoradionecrosis Following Post-Operative Intensity-Modulated Radiation Therapy and Proton Therapy for Oral Cavity Cancer. ASTRO, San Francisco, CA, 2025.

[142] Oh JH, Pareja F, Elkin R, Xu K, Norton L, and Deasy JO. Biological features relevant to poor prognosis in breast cancer. DTE - AICOMAS, Paris, France, 2025.

[141] Lee D, Teeradon T, Hu Y, Zhang P, Oh JH, Aristophanous M, Cerviño L, and Zhang P. Development of a deep learning deformable image registration algorithm for adaptive radiotherapy of head and neck cancer. ESTRO, Vienna, Austria, 2025.

[140] JH Oh, Kerns S, Hall W, Lee S, Rosenstein BS, and Deasy JO. Predicting radiotherapy-induced erectile dysfunction in prostate cancer patients using a germline genetic neural network model. ESTRO, Vienna, Austria, 2025.

[139] Simhal AK, Firestone R, Oh JH, Norton L, Hultcrantz M, Usmani SZ, Deasy JO, and Maclachlan KH. High WEE1 expression correlates with poor survival in multiple myeloma. ASH, San Diego, CA, 2024.

[138] Schwartz CJ, Oh JH, Rana S, Repetto M, Gazzo A, Shen S, Zhang H, Ross A, Wen H, Weigelt B, Norton L, Brogi E, Terraf P, and Pareja F. Genomic and Clinicopathologic Profiling of Breast Invasive Lobular Carcinoma in Patients with Germline Predisposition. San Antonio Breast Cancer Symposium. San Antonio, TX, 2024. 1. Lobular Breast Cancer Alliance Research Abstract Merit Award

[137] Simhal AK, Firestone R, Oh JH, Maclachlan KH, Norton L, Usmani SZ, and Deasy JO. Increased WEE1 expression is predictive of short progression-free survival, independent of standard prognostic factors in multiple myeloma. IMS, Rio De Janeiro, Brazil, 2024.

[136] Watt GP, Reiner AS, Shu X, Malone KE, Knight JA, John EM, Chow EJ, Lynch CF, Mellemkjær L, Woods M, Liang X, Tran AP, Oh JH, Derkach A, the WECARE Study Collaborative Group, Bernstein JL. Polygenic risk of coronary artery disease for long-term survivors of breast cancer. IGES/ASHG, Denver, CO, 2024.

[135] Oh JH, Pareja F, Elkin R, Norton L, and Deasy JO. A higher-risk breast cancer subtype is associated with increased hypoxia scores and lower tumor-infiltrating lymphocytes. ISMB, Montreal, Canada, 2024.

[134] Askarifirouzjaei H, Oh JH, Han D, Qi H, Lin H, Hasan S, Baltaci M, Russell J, Powell SN, Humm J, Deasy JO, and Haimovitz-Friedman A. Regulation of Immunosuppressive PD-L1 Expression by Homologous Recombination Repair in Proton vs. Photon Therapy. RRS, Tucson, AZ, 2024.

[133] Askarifirouzjaei H, Oh JH, Han D, Qi H, Lin H, Hasan S, Baltaci M, Russell J, Powell SN, Humm J, Deasy JO, and Haimovitz-Friedman A. Temporal single-cell RNA-Seq analysis in HRR-proficient and HRR-deficient colorectal tumor cells in response to radiation. RRS, Tucson, AZ, 2024.

[132] Askarifirouzjaei H, Oh JH, Han D, Qi H, Lin H, Hasan S, Baltaci M, Russell J, Powell SN, Humm J, Deasy JO, and Haimovitz-Friedman A. Radiosensitization with Spironolactone increases more with proton radiation as compared to photon radiation. RRS, Tucson, AZ, 2024.

[131] Simhal AK, Firestone RS, Oh JH, Maclachlan KH, Norton L, Mitsiades CS, Usmani SZ, and Deasy JO. Increased WEE1 expression correlates with poor survival in multiple myeloma independent of common prognostic factors. EHA, Madrid, Spain, 2024.

[130] Rogowski V, Jamtheim Gustafsson C, Gebre-Medhin M, Oh JH, Munck af Rosenschold P, and Änghede Haraldsson A. Statistical Analysis of Side Effects in Head and Neck Cancer Patients from ARTSCAN III trial. ESTRO, Glasgow, UK, 2024.

[129] Oh JH, Rizzuto G, Elkin R, Dveksler G, Tannenbaum A, and Deasy JO. Gene expression of pregnancy-specific glycoproteins correlates with poor survival outcomes for female patients with lung cancer. The 31st Annual International CEA Symposium, New York, NY, 2023.

[128] Simhal AK, Maclachlan KH, Usmani SZ, Norton L, Deasy JO, Oh JH, and Tannenbaum A. Network modeling of apoptosis-related genes reveal a high-risk cluster in multiple myeloma. ASH, San Diego, CA, 2023.

[127] Oh JH, Lee S, Thor M, Rosenstein BS, Tannenbaum A, Deasy JO, and Kerns S. Machine learning to identify prostate cancer patients at risk of post-radiotherapy hematuria. ICRR, Montreal, Canada, 2023.

[126] Oh JH, Apte A, Veeraraghavan H, Tannenbaum A, and Deasy JO. A Radiomic Network Analysis Can Identify Survival Outcomes and Relevant Tumor Immune Infiltrates in Non-Small Cell Lung Cancer. AAPM, Houston, TX, 2023.

[125] Oh JH, Lee S, Thor M, Rosenstein BS, Tannenbaum A, Kerns S, and Deasy JO. A Machine Learning Prediction Model for Post-Radiotherapy Hematuria Based on a Genome-Wide Association Study. AAPM, Houston, TX, 2023.

[124] Aliotta E, Paudyal R, Diplas B, Han J, Hatzoglou V, Jensen N, Zhang P, Oh JH, Aristophanous M, Riaz N, Deasy J, Lee N, and Shukla-Dave A. Imaging Markers Associated with Rapid Response to Head and Neck Radiotherapy. AAPM, Houston, TX, 2023.

[123] Oh JH, Veeraraghavan H, Apte A, Tannenbaum A, and Deasy JO. Tumor immune infiltrates and overall survival in non-small cell lung cancer are associated with an unsupervised radiomic signature. ASCO, Chicago, IL, 2023.

[122] Simhal A, Maclachlan K, Elkin R, Zhu J, Usmani SZ, Keats J, Norton L, Deasy JO, Oh JH, and Tannenbaum A. Ollivier-Ricci curvature-based RNA-sequencing data analysis uncovers an under-surviving subtype in multiple myeloma. AACR, Orlando, FL, 2023.

[121] Murgas K, Oh JH, Deasy JO, and Tannenbaum A. Topological data analysis reveals pan-cancer immune phenotypes with immune-related survival differences. AACR, Orlando, FL, 2023.

[120] Elkin R, Oh JH, Dela Cruz F, Norton L, Deasy JO, Kung AL, and Tannenbaum A. Geometry of gene expression network reveals a potential novel indicator in Ewing sarcoma. AACR, Orlando, FL, 2023.

[119] Zhu J, Oh JH, Simhal A, Elkin R, Norton L, Deasy JO, and Tannenbaum A. Deep Neural Networks using protein-protein network information predict Multiple Myeloma Survival. AACR, Orlando, FL, 2023.

[118] Simhal A, Maclachlan K, Elkin R, Zhu J, Usmani S, Keats J, Norton L, Deasy JO, Oh JH, and Tannenbaum A. Geometric network analysis defines poor-prognosis subtypes in multiple myeloma. ASH Annual Meeting, New Orleans, LA, 2022.

[117] Oh JH, Tannenbaum A, and Deasy JO. Automatic identification of drug-induced liver injury literature using natural language processing and machine learning methods. CAMDA 2022, Wisconsin, WI, 2022.

[116] Simhal A, Maclachlan K, Elkin R, Zhu J, Usmani S, Deasy JO, Oh JH, and Tannenbaum A. Network topology analysis reveals unique multiple myeloma genomic subtypes and potential new therapeutic targets. 19th International Myeloma Society Annual Meeting, Los Angeles, CA, 2022.

[115] Oh JH, Lee S, Kerns S, Thor M, Apte A, Higginson D, and Deasy JO. Machine learning-based modeling using genome-wide SNPs to predict radiosensitivity. Radiation Research Society, Hawaii, 2022.

[114] Veeraraghavan H, Oh JH, Zhu J, Jiang J, Tannenbaum A, Gomez D, and Deasy JO. Beating the curse of dimensionality: applying unbalanced optimal transport clustering of delta radiomics to predict survival outcomes in lung cancer patients treated with immunotherapy. AAPM, Washington, DC, 2022.

[113] Apte A, Iyer A, LoCastro E, Veeraraghavan H, Oh JH, and Deasy JO. STRATIS: A cloud- enabled Software Toolbox for RAdioTherapy and Imaging analysis. AAPM, Washington, DC, 2022.

[112] Oh JH, Veeraraghavan H, Katsoulakis E, Apte A, Zhu J, Yu Y, Lee N, Hatzoglou V, Tannenbaum A, Riaz N, and Deasy JO. A Radiogenomics study using a network-based unbalanced optimal mass transport method in head and neck squamous cell carcinoma. AAPM, Washington, DC, 2022.

[111] Diplas BH, Han J, Paudyal R, Oh JH, Sherman E, Schoder H, Hatzoglou V, Yu Y, Wong RJ, Wray R, Boyle JO, Grkovski M, Humm J, Dave A, Riaz N, and Lee N. Intra-Treatment Tumor Apparent Diffusion Coefficient, a Quantitative Imaging Metric, is Associated with Neck Nodal Recurrence in De-Escalated Treatment of HPV-Positive Oropharyngeal Cancer (OPC). ASTRO, San Antonio, TX, 2022. 

[110] Han JE, Diplas BH, Paudyal R, Oh JH, Sherman E, Schöder H, Wong RJ, Wray R, Boyle J, Grkovski M, Humm JL, Shukla-Dave A, Riaz N, and Lee N. Tumor Volume Predicts for Baseline Hypoxia Status in HPV related Oropharyngeal Carcinomas (OPC) that Underwent Major Radiation De-escalation, the 30 Reduction in Oropharyngeal Cancer Trial. ASTRO, San Antonio, TX, 2022.

[109] Thor M, Zhu J, Apte A, Tran P, Oh JH, Shepherd A, Rimner A, Tannenbaum A, and Deasy JO. A non-parametric dose model to identify pericardial subregions associated with high-risk of death in RTOG 0617 and exploration in an external cohort. ESTRO, Copenhagen, Denmark, 2022.

[108] Oh JH, Apte AP, Iyer A, Tannenbaum A, and Deasy JO. Radiomic analysis of limited-sized data using unsupervised methods: Prediction of HPV status in head and neck cancer. AAPM, Columbus, OH, 2021.

[107] Zhu J, Thor M, Apte A, Oh JH, Rimner A, Deasy JO, and Tannenbaum A. A non-parametric analysis to identify high-risk vs. low risk anatomic regions associated with reduced overall survival in the RTOG 0617 clinical trial data. AAPM, Columbus, OH, 2021.

[106] Thor M, Zhu J, Apte A, Oh JH, Rimner A, Deasy JO, and Tannenbaum A. Using unbalanced optimal mass transport to estimate thoracic dose distributions associated with risk of death in RTOG 0617. ASTRO, Chicago, 2021.

[105] Paudyal R, Chen L, Oh JH, Zakeri K, Hatzoglou V, Tsai CJ, Lee N, and Shukla-Dave A. Non-gaussian IVIM DW-and fast exchange regime DCE- MRI for predicting of locoregional failure in nasopharyngeal carcinoma. ISMRM, Vancouver, Canada, 2020.

[104] Konar AS, Shah AD, Paudyal R, Oh JH, LoCastro E, Aramburu Nunez D, Swinburne N, Young RJ, Holodny AI, Beal K, Hatzoglou V, and Shukla-Dave A. Diffusion and perfusion MRI predicts response preceding and shortly after stereotactic radiosurgery to brain metastases. ISMRM, Vancouver, Canada, 2020.

[103] Paudyal R, Grkovski M, Schöder H, Oh JH, Aramburu Nunez D, Hatzoglou V, Deasy JO, Humm JL, Lee N, and Shukla-Dave A. Correlation assessment between quantitative multimodality imaging metrics using a community detection algorithm. ISMRM, Vancouver, Canada, 2020.

[102] Apte A, Iyer A, Deasy J, and Oh JH. Understanding radiomics interconnections using network graphs. AAPM, Vancouver, Canada, 2020.

[101] Apte A, Oh JH, Haq R, Iyer A, Pandya R, Deasy JO, and Thor M. Mapping cardiac dose to reference anatomy to explore relationship with overall survival in RTOG0617 trial. AAPM, Vancouver, Canada, 2020.

[100] Oh JH, Apte A, Katsoulakis E, Riaz N, Hatzoglou V, Yu Y, Mahmood U, Pouryahya M, Iyer A, Dave A, Lee N, and Deasy J. Reproducibility test of radiomic features using regularized partial correlation network. AAPM, Vancouver, Canada, 2020.

[99] Thor M, Apte A, Haq R, Pandya R, Iyer A, Oh JH, and Deasy J. Dose to the left ventricle and the right atrium as well as mean lung dose predicts overall survival in RTOG 0617: an updated and more detailed cardiopulmonary dose-response model. AAPM, Vancouver, Canada, 2020.

[98] Mahmood U, Apte A, Kanan C, Bates D, Corrias G, Mannelli L, Oh JH, Erdi Y, Deasy J, and Dave A. From CT scans to 3D prints: Feasibility of 3D printing CT Radiomic Phantoms for Standardization and Validation of Quantitative CT Measurements. AAPM, Vancouver, Canada, 2020.

[97] Thor M, Fitzgerald K, Apte A, Oh JH, Iyer A, Nadeem S, Chaft J, Wu A, Offin M, Gelblum D, Deasy JO, and Rimner A. A pre-treatment PET and CT-derived model for progression-free survival in early stage non-small cell lung cancer. ASTRO, Miami Beach, Florida, 2020.

[96] Paudyal R, Oh JH, Hatzoglou V, Moreira AL, Shaha AR, Tuttle M, and Shukla-Dave A. Predicting tumor aggressiveness in papillary thyroid cancers using multiparametric quantitative imaging metrics. ISMRM, Sydney, Australia, 2020.

[95] Oh JH, Katsoulakis E, Riaz N, Yu Y, Apte AP, Leeman JE, Katabi N, Morris L, Chan TA, Hatzoglou V, Lee NY, and Deasy JO. Radiomics characteristics correlate with immune activation and HPV status in head and neck cancer. ESTRO, Vienna, Austria, 2020.

[94] Sanduleanu S, Jochems A, Upadhaya T, Even AJG,  Leijenaar RTH, Dankers FJWM, Klaassen R, Woodruff HC, Hatt M, Kaanders HJAM, Hamming-Vrieze O, van Laarhoven HWM, Subramiam RM, Huang SH, O'Sullivan B, Bratman SV, Dubois LJ,  Miclea RL, Di Perri D, Geets X, Crispin-Ortuzar M, Apte A, Deasy JO, Oh JH,  Lee NY, Humm JL, Schöder H, De Ruysscher D, Hoebers F, and Lambin P. Non-invasive radiomic imaging prediction of tumor hypoxia: a potential biomarker for FLASH irradiation? ESTRO, Vienna, Austria, 2020.

[93] Pouryahya M, Oh JH, Javanmard P, Mathews JC, Belkhatir Z, Deasy JO, and Tannenbaum AR. Integrative Network-based Clustering of Multiomics Data for Subtype Analysis of Breast and Lung Cancer. ISMB, Basel, Switzerland, 2019.

[92] Oh JH, Lee S, Liang X, Woods M, Reiner A, The WECARE Study Collaborative Group, Deasy JO, and Bernstein JL. Machine learning-based modeling of radiation-associated contralateral breast cancer in the WECARE Study. ISMB, Basel, Switzerland, 2019.

[91] Wang J, Oh JH, and Li R. Integrating Radiomics and Genomics for Personalized Cancer Therapy in the Era of AI and Big Data. Presentation Title: Genetic Risk Modeling Using Machine Learning to Predict Radiotherapy Complications and Identify Key Biological Correlates. AAPM, San Antonio, TX, 2019.

[90] Iyer A, Oh JH, Thor M, Deasy JO, and Apte AP. Standardizing patient orientation to improve generalization of radiomics models. AAPM, San Antonio, TX, 2019.

[89] Thor M, Fitzgerald K, Iyer A, Apte A, Oh JH, Deasy JO, Chaft J, Offin M, Wu A, Gelblum D, and Rimner A. Predicting tumor progression in early stage non-small cell lung cancer using pre-treatment imaging. ASTRO, Chicago, IL, 2019.

[88] Pandya R, Iyer A, Apte A, Elguindi S, Veeraraghavan H, Thor M, Oh JH, and Deasy JO. CERR's Model Implementation Library for sharing radiomics and image segmentation models. ICCR, Montreal, Canada, 2019.

[87] Lee S, Deasy JO, Oh JH, Di Meglio A, Boyault S, Rousseau M,  Besse C, Thomas E,  Boland A, Cottu P, Tredan O, Levy C, Martin A-L, Everhard S, Ganz P, Partridge A, Michiels S, Deleuze J-F, Andre F, and Luis IV. Prediction of Treatment (tx)-Induced Fatigue in Breast Cancer (BC) patients (pts) using Machine Learning on Genome Wide Association (GWAS) Data in the prospective CANTO cohort. ASCO, Chicago, IL, 2019.

[86] Paudyal R, Oh JH, Leeman J, Song X, Shridhar AK, LoCastro E, Hatzoglou V, Riaz N, Lee N, and Shukla-Dave A. Non-Gaussian intravoxel incoherent motion diffusion-weighted imaging for prediction of local control in nasopharyngeal carcinoma. ISMRM, Montreal, Canada, 2019.

[85] Oh JH, Lee S, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. Machine learning to design genetic models of radiation-induced complications in prostate cancer patients following radiotherapy. 30th Anniversary AACR Special Conference Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer, Newport, RI, 2018.

[84] Pouryahya M, Mathews JC, Belkhatir Z, Tannenbaum AR, Oh JH, and Deasy JO. Heterogeneous network-based analysis for characterizing drug response and biological targets. 30th Anniversary AACR Special Conference Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer, Newport, RI, 2018.

[83] Apte A, Iyer A, van Dijk L, Thor M, Veeraraghavan H, Fontenla S, Oh JH, Mechalakos J, Hunt M, and Deasy JO. Bagged Atlas Based Segmentation (BABS): bagging atlas segmentations from multiple image representations. Annual Meeting of The American Association of Physicists in Medicine, Nashville, TN, 2018.

[82] Iyer A, Fontenla S, Haq R, Veeraraghavan H, Oh JH, Mechalakos JG, Hunt M, Deasy JO, and Apte A. Machine learning-based post-processing method for improved segmentation of parotid glands. Annual Meeting of The American Association of Physicists in Medicine, Nashville, TN, 2018.

[81] Iyer A, Jackson A, Apte A, Thor M, Fontanella A, Oh JH, and Deasy JO. Updates to radiotherapy outcomes estimator (ROE) for protocol comparison and display of clinical constraints. Annual Meeting of The American Association of Physicists in Medicine, Nashville, TN, 2018.

[80] Oh JH, Katsoulakis E, Leeman J, Yu Y, Tsai J, McBride S, Katabi N, Apte A, Lee N, Hatzoglou V, Riaz N, and Deasy JO. Radiomics characteristics correlate with immune activation: A TCIA/TCGA data analysis in head and neck squamous cell carcinoma. Annual Meeting of The American Association of Physicists in Medicine, Nashville, TN, 2018.

[79] Zarepisheh M, Hong L, Zhou Y, Oh JH, Mechalakos JG, Hunt MA, Mageras GS, and Deasy JO. Automated IMRT treatment planning using expedited constrained hierarchical optimization (ECHO): retrospective and prospective study. Annual Meeting of The American Association of Physicists in Medicine, Nashville, TN, 2018.

[78] Katsoulakis E, Oh JH, Leeman J, Yu Y, Tsai J, McBride S, Katabi N, Apte A, Deasy J, Lee N, Hatzoglou V, and Riaz N. Identifying biological subtypes of Head and Neck Squamous Cell Carcinoma (HNSCC) from contrast enhanced CT scans using Radiomics and The Cancer Genome Atlas (TCGA). Annual meeting of American Society for Radiation Oncology, San Antonio, TX, 2018.

[77] Thor M, Deasy JO, Hu C, Choy H, Komaki R, Masters G, Blumeschein G, Forster K, Oh JH, Kavadi V, Narayan S, Timmerman R, Robinson C, Greenberger JS, Biggs D, Augspurger M, Meng J, and Bradley J. The role of heart-related dose-volume metrics on overall survival in the RTOG 0617 clinical trial. Annual meeting of American Society for Radiation Oncology, San Antonio, TX, 2018.

[76] Lee S, Kerns S, Rosenstein B, Ostrer H, Oh JH, and Deasy JO Predicting congenital late genitourinary toxicity by machine learning on genome-wide single nucleotide polymorphism data. ESTRO, Barcelona, Spain, 2018.

[75] Lee S, Kerns S, Rosenstein B, Ostrer H, Deasy JO, and Oh JH. Preconditioned Random Forest Regression: Application to Genome-Wide Study for Radiotherapy Toxicity Prediction. ACM BCB, Boston, MA, 2017.

[74] Choi W, Liu C, Alam SR, Oh JH, Adusumilli P, Weber W, Deasy JO, and Lu W. Aggressive lung adenocarcinoma subtype prediction using FDG-PET/CT radiomics. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[73] Lee S, Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. Machine learning-based modeling to predict radiotherapy-induced genitourinary toxicity in prostate cancer using genome-wide association study. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[72] Apte A, Veeraraghavan H, Mahmood U, Oh JH, Fontenla S, and Deasy JO. Organ specific eigen-texture for atlas based segmentation. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[71] Jeong J, Oh JH, Crispin-Ortuzar M, and Deasy JO. Comparison between mechanistic radiobiological modeling vs. Fowler BED equation in evaluating lung cancer radiotherapy outcome for a broad range of fractionation. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[70] Oh JH, Folkert M, Setton J, Apte A, Grkovski M, Young R, Schoder H, Thorstad W, Lee N, and Deasy JO. PET-based radiomics to predict outcomes following definitive chemoradiotherapy for oropharyngeal cancer. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[69] Crispin-Ortuzar M, Apte A, Grkovski M, Oh JH, Lee N, Humm J, and Deasy JO. Using FDG PET and CT radiomics features to predict FMISO uptake in head and neck cancer. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[68] Choi W, Oh JH, Alam SR, Jiang F, Chen W, Deasy JO, and Lu W. Radiomics analysis of pulmonary nodules in low dose CT for early detection of lung cancer. Annual Meeting of The American Association of Physicists in Medicine, Denver, CO, 2017.

[67] Taunk NK, Oh JH, Dave A, Beal K, Vachha B, Holodny A, and Hatzoglou V. Early posttreatment assessment of MRI perfusion biomarkers can predict long-term response of NSCLC brain metastases to SRS: A longitudinal analysis. Annual meeting of American Society for Radiation Oncology, San Diego, CA, 2017.

[66] Crispin-Ortuzar M, Apte A, Grkovski M, Oh JH, Lee NY, Humm J, and Deasy JO. Combined FDG and CT radiomics features predict FMISO uptake in head and neck cancer. Annual meeting of American Society for Radiation Oncology, San Diego, CA, 2017.

[65] Deasy JO, Thor M, Oh JH, and Rimner A. New NTCP data in the thoracic region: probing 'dark toxicity'. ESTRO, Vienna, Austria, 2017.

[64] Thor M, Olsson CE, Oh JH, Pauli N, Pettersson N, Finizia C, and Deasy JO. Is radiation-induced trismus a time dependent masticatory structure story? ESTRO, Vienna, Austria, 2017.

[63] Paudyal R, Oh JH, Riaz N, Venigalla P, Li J, Hatzoglou V, Leeman J, Nunez DA, Lu Y, Deasy JO, Lee N, and Shukla-Dave A. Intravoxel incoherent motion diffusion-weighted MRI during chemoradiation therapy to monitor treatment response in human papillomavirus head and neck squamous cell carcinoma. ISMRM, Hawaii, USA, 2017.

[62] Dashevsky BZ, Oh JH, Apte A, Morris EA, Deasy JO, and Sutton EJ. MRI features predictive of negative surgical margins in patients with HER2 overexpressing breast cancer undergoing breast conservation. RSNA, Chicago, USA, 2016.

[61] Tyagi N, Sutton E, Hunt M, Apte A, Zhang J, Oh JH, Mechalakos J, Mehrara B, Matros E, and Ho A. Morphological features of MRI as a correlate of capsular contracture in breast cancer patients with implant-based reconstructions. Annual Meeting of The American Association of Physicists in Medicine, Washington, DC, 2016.

[60] Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. Integration of machine learning and bioinformatics methods to analyze genome-wide association study data for rectal bleeding and erectile dysfunction following radiotherapy in prostate cancer. Annual Meeting of The American Association of Physicists in Medicine, Washington, DC, 2016.

[59] Thor M, Owosho AA, Rosenberg H, Yom SHK, Oh JH, Riaz N, Tsai J, Lee NY, Huryn JM, Estilo CL, and Deasy JO. Exploring and refining the QUANTEC guideline to reduce hyposalivation/xerostomia following intensity-modulated radiotherapy for head and neck cancer. Annual Meeting of The American Association of Physicists in Medicine, Washington, DC, 2016.

[58] Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. A machine learning model to predict the risk of rectal bleeding and erectile dysfunction following radiotherapy in prostate cancer. 18th International Conference on the use of Computers in Radiation Therapy, London, UK, 2016.

[57] Apte AP, Veeraraghavan H, Fehr D, Oh JH, and Deasy JO. The texture toolbox for image auantification. 18th International Conference on the use of Computers in Radiation Therapy, London, UK, 2016.

[56] von Reibnitz D, Yorke ED, Oh JH, Apte A, Wu AJ, Fleisher M, Gelb E, Deasy J, and Rimner A. Alpha-2-Macroglobulin as a radioprotective factor in patients undergoing thoracic radiation. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2016.

[55] Gay HA, Deasy JO, Apte AP, Daly MD, Adkins DR, Rich J, Michel L, Wildes TM, Dyk P, Mullen DF, Eschen L, Chin RI, Nussenbaum B, Haughey BH, Thorstad WL, and Oh JH. Predictors of acute throat or esophageal pain during radiotherapy for head and neck cancer. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2016.

[54] Thor M, Olsson C, Oh JH, Pauli N, Johansson M, Deasy JO, and Finizia C. What to ask and when to act - associations between patient-reported trismus and mouth-opening distances after radiotherapy for head and neck cancer. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2016.

[53] Paudyal R, Riaz N, Oh JH, Venigalla P, Li J, Hatzoglou V, Aramburu Nunez D, Lu Y, Deasy JO, Lee N, and Shukla-Dave A. Characterization of HPV positive oropharyngeal tumors using intravoxel incoherent motion DW-MRI before and during radiation therapy. ISMRM, Singapore, 2016.

[52] Dashevsky BZ, Oh JH, Apte AP, Sutton EA, Deasy JO, and Morris EJ. MRI features can be used to predict success of breast conservation in patients with HER2+ breast cancer. SBI/ACR Breast Imaging Symposium, Austin, TX, 2016.

[51] Thor M, Olsson C, Oh JH, Hedström J, Pauli N, Deasy JO, and Finizia C. Temporal patterns of patient-reported trismus domains after radiotherapy for head and neck cancer and associated mouth-opening distances. ESTRO, Turin, Italy, 2016.

[50] Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. A novel multi-SNP model predictive of erectile dysfunction following radiotherapy in prostate cancer. ESTRO, Turin, Italy, 2016.

[49] Thor M, Olsson CE, Deasy JO, Alsadius D, Pettersson N, Waldenström AC, Steineck GN,  and Oh JH. Dose-Response Relationships for Four Gastrointestinal Symptom Groups in Prostate Cancer Radiation Therapy. Annual meeting of American Society for Radiation Oncology, San Antonio, TX, 2015.

[48] Robinson C, Fontanella A, Abraham C, Oh JH, Apte A, Mullen D, and Deasy JO. Validating a mechanistic tumor control probability (TCP) model applied to non-small cell lung cancer (NSCLC) brain metastases treated with single fraction radiosurgery (SRS). Annual meeting of American Society for Radiation Oncology, San Antonio, TX, 2015.

[47] Thor M, Olsson CE, Oh JH, Petersen SE, Alsadius D, Muren LP, Pettersson N, Bentzen L, Høyer M, Steineck G, and Deasy JO. Radiation dose to the gastro-intestinal (GI) tract and patient-reported symptom domains after prostate cancer radiotherapy. BiGART, Aarhus, Denmark, 2015. 

[46] Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. A machine learning method to build multi-SNP predictive models of clinical radiosensitivity. IUPSEM, Toronto, Canada, 2015.

[45] Apte A, Veeraraghavan H, Oh JH, Kijewski P, and Deasy JO. The radiomics toolbox in the computational environment for radiological research (CERR). Annual Meeting of The American Association of Physicists in Medicine, Anaheim, CA, 2015.

[44] Oh JH, Sutton EJ, Veeraraghavan H, Apte AP, Morris EA, and Deasy JO. Radiomics and radiogenomics for breast cancer using magnetic resonance imaging. Annual Meeting of The American Association of Physicists in Medicine, Anaheim, CA, 2015.

[43] Cella L, Oh JH, Deasy JO, Conson M, Picardi M, Pressello MC, Boboc G, Battistini R, Donato V, and Pacelli R. Machine learning-based prediction of late radiation-induced lung toxicity in Hodgkin's lymphoma survivors. ESTRO, Barcelona, Spain, 2015.

[42] Oh JH, Kerns S, Ostrer H, Rosenstein B, and Deasy JO. A machine learning method demonstrates that a large number of SNPs contribute to clinical radiosensitivity. ESTRO, Barcelona, Spain, 2015.

[41] Thor M, Olsson CE, Oh JH, Hansen S, Petersen PM, Lindberg H, Kempel MM, Dysager L, Høyer M, Deasy JO, and Bentzen L,  Temporal patterns of patient-reported symptom groups after prostate cancer radiotherapy. ESTRO, Barcelona, Spain, 2015.

[40] Thor M, Olsson C, Oh JH, Alsadius D, Pettersson N, Deasy JO, and Steineck G. Is corpora cavernosa a critical structure for sexual dysfunction in prostate cancer radiotherapy? ESTRO, Barcelona, Spain, 2015.

[39] Thor M, Olsson C, Oh JH, Petersen SE, Alsadius D, Høyer M, Pettersson N, Bentzen L, Deasy JO, Muren LP, and Steineck G. Predicting radiation-induced patient-reported genitourinary toxicity in four prostate cancer cohorts. ESTRO, Barcelona, Spain, 2015.

[38] Olsson C, Thor M, Oh JH, Petersen SE, Alsadius D, Høyer M, Pettersson N, Waldenström AC, Bentzen L, Deasy JO, Muren LP, and Steineck G. Is the anal sphincter a key structure for gastrointestinal toxicity in prostate cancer radiotherapy? ESTRO, Barcelona, Spain, 2015.

[37] Thakur SB, Oh JH, Soledad M, Veeraraghavan H, Gnanasigamani MM, Sutton EJ, Deasy JO, and Morris E. Evaluation of benign and high-risk, nonmalignant breast lesions, assessed as false-positive at contrast-enhanced (CE) MRI using DW imaging and CE MR imaging features. ISMRM, Toronto, Canada, 2015.

[36] Sutton EJ,  Oh JH, Dashevsky B, Veeraraghavan H, Deasy JO, and Morris EA. Association between Oncotype Dx® Breast Cancer 21-gene Assay Recurrence Score and Computer-derived imaging features. RSNA, Chicago, USA, 2014.

[35] Sutton EJ, Dashevsky B, Oh JH, Veeraraghavan H, Morris EA, and Deasy JO. Classification of breast cancer subtypes using MRI texture features. RSNA, Chicago, USA, 2014.

[34] Thor M, Olsson C, Oh JH, Petersen S, Alsadius D, Høyer M, Pettersson N, Bentzen L, Deasy JO, Muren L, and Steineck G. Identifying Groups of Patient-Reported Gastro-Intestinal Symptoms Using Factor Analysis. Annual meeting of American Society for Radiation Oncology, San Francisco, CA, 2014.

[33] Kohutek Z, Oh JH, Apte AP, Folkert MR, Foster A, Wu AJ, Deasy JO, and Rimner A. Predictive modeling of outcomes following SBRT for non-small cell lung cancer using FDG-PET image statistical and texture characteristics. Annual meeting of American Society for Radiation Oncology, San Francisco, CA, 2014.

[32] Thakur S, Annarao S, Bokacheva L, and Oh JH. Measurement of lactate concentrations in the breast mammary tumors using selective multiple quantum coherence editing sequence at 4.7T. Joint Annual Meeting ISMRM-ESMRMB, Milano, Italy, 2014.

[31] Sutton EJ, Morris EA, Morrow M, Stempel M, Shukla-Dave A, Oh JH, Deasy JO, and Mazaheri Y. Contrast-enhanced MR features of triple-negative breast carcinomas (TNBC) associated with high histological grade. Joint Annual Meeting ISMRM-ESMRMB, Milano, Italy, 2014.

[30] Jeong J, Oh JH, Rao S, and Deasy JO. Is "new radiobiology" needed to account for the anti-tumor efficacy of hypofractionated lung SBRT?. Annual Meeting of The American Association of Physicists in Medicine, Austin, TX, 2014.

[29] Gay H, Oh JH, Apte A, Dyk P, Mullen D, Eschen L, Fergus S, Chin RI, Thorstad W, and Deasy JO. Investigation of the association between radiation-induced pain and radiation dose in head and neck cancer patients. Annual Meeting of The American Association of Physicists in Medicine, Austin, TX, 2014.

[28] Thor M, Saleh Z, Oh JH, Apte A, Muren L, and Deasy JO. Estimating plausible treatment course dose distributions by accounting for registration uncertainty and organ motion. Annual Meeting of The American Association of Physicists in Medicine, Austin, TX, 2014.

[27] Oh JH and Deasy JO. Prediction of late radiation-induced proctitis in prostate cancer patients using chromosome aberration and cell proliferation rate. Annual Meeting of The American Association of Physicists in Medicine, Austin, TX, 2014.

[26] Oh JH, Apte A, Folkerts M, Kohutek Z, Wu A, Rimner A, Lee N, and Deasy JO. FDG-PET-based radiomics to predict local control and survival following radiotherapy. Annual Meeting of The American Association of Physicists in Medicine, Austin, TX, 2014. Press Release and Press Conference featuring outstanding newsworthy science. RSNA News: https://www.rsna.org/news/2015/february/radiomics-could-change-role-of-radiologists

[25] Thor M, Olsson C, Petersen SE, Alsadius D, Hoyer M, Pettersson N, Bentzen L, Oh JH, Deasy JO, Muren LP, and Steineck G. Identifying relationships between patient-reported outcomes in multiple radiotherapy cohorts. ESTRO, Vienna, Austria, 2014.

[24] Goodman K, Riedel E, Tom A, Oh JH, Kelvin JF, Thom B, and Law E.  Prospective study of vaginal dilator use following pelvic radiotherapy for gastrointestinal malignancies. Annual meeting of American Society for Radiation Oncology, Atlanta, GA, 2013.

[23] Rothenstein D, Oh JH, Apte AP, Deasy JO, and Goodman KA. Predictors of outcome and gastrointestinal and hematologic toxicities during intensity modulated radiotherapy. Annual meeting of American Society for Radiation Oncology, Atlanta, GA, 2013.

[22] Yang TJ, Oh JH, Folkert MR, Morikawa A, Seidman AD, Yamada Y, Chan TA, and Beal K. Prognostic implications of receptor status and extracranial disease in patients with breast cancer brain metastases treated with stereotactic radiosurgery. Annual meeting of American Society for Radiation Oncology, Atlanta, GA, 2013.

[21] Yang TJ, Oh JH, Folkert MR, and Beal K. Concurrent tratuzumab in patients with her2 positive cancer undergoing definitive stereotactic radiosurgery for brain metastasis. Annual meeting of American Society for Radiation Oncology, Atlanta, GA, 2013.

[20] Folkert MR, Oh JH, Setton J, Apte AP, Thorstad WL, Schoder H, Lee NY, and Deasy JO. Predictive modeling of outcomes following definitive chemoradiotherapy for oropharyngeal cancer based on FDG-PET image characteristics. Annual meeting of American Society for Radiation Oncology, Atlanta, GA, 2013. The Resident Clinical/Basic Science Research Abstract Award

[19] Oh JH and Deasy JO. Prediction of multi-categorical radiation pneumonitis status in lung cancer patients using machine learning approaches. Annual Meeting of The American Association of Physicists in Medicine, Indianapolis, IN, 2013.

[18] Oh JH, Stoyanova R, Deasy JO, Saleh Z, Buyyounouski MK, Price RA, Hu JJ, and Pollack A. Identification of a single nucleotide polymorphism associated with sexual dysfunction in prostate cancer patients. ESTRO Forum, Geneva, Switzerland, 2013.

[17] Yang T, Oh JH, Son C, Apte A, Deasy JO, and Goodman KA. Predictors of gastrointestinal toxicity during pelvic radiotherapy. Gastrointestinal Cancers Symposium, San Francisco, CA, 2013.

[16] Son C, Law E, Oh JH, Apte AP, Yang TJ, Deasy JO, and Goodman KA. Dosimetric predictors of radiation-induced vaginal stenosis in rectal and anal cancer patients. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2012.

[15] Yang T, Oh JH, Apte A, Son CH, Deasy JO, and Goodman KA. Predictors of hematologic toxicity during pelvic radiation therapy. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2012.

[14] Oh JH, Riaz N, Jaffray S, Estilo CL, Lee RS, Katsoulakis E, Apte A, Huryn JM, Lee N, and Deasy JO. A novel modeling for salivary toxicity based on salivary flow recovery over time in head-and-neck cancer patients treated with radiation therapy. Annual meeting of American Society for Radiation Oncology, Boston, MA, 2012.

[13] Estilo CL, Lee RS, Williams T, Oh JH, Apte A, Huryn JM, Lee N, and Deasy JO. Parotid gland and oral cavity sparing vs. salivary function following intensity-modulated radiation therapy for head and neck cancer. Multinational Association of Supportive Care in Cancer, New York, NY, 2012.

[12] Apte A, Wang Y, Oh JH, Saleh Z, and Deasy JO. CERR: new tools to analyze image registration precision. Annual Meeting of The American Association of Physicists in Medicine, Charlotte, NC, 2012.

[11] Oh JH, Wang Y, Apte A, and Deasy JO. A Statistical and machine learning-based tool for modeling and visualization of radiotherapy treatment outcomes. Annual Meeting of The American Association of Physicists in Medicine, Charlotte, NC, 2012.

[10] Oh JH, Apte A, Robinson C, Bradley JD, and Deasy JO. Improved predictive modeling of radiation pneumonitis in lung cancer patients using machine learning techniques. Annual Meeting of The American Association of Physicists in Medicine, Charlotte, NC, 2012.

[9] El Naqa I, Bradley JD, Oh JH, Craft JM, and Deasy JO. Investigating alpha-2-macroglobulin and its dosimetric interactions for predicting radiation pneumonitis. Annual meeting of American Society for Radiation Oncology, Miami, FL, 2011.

[8] Oh JH, Deasy JO, Stoyanova R, Saleh Z, Buyyounouski M, Wong HP, Apte A, Price RA, Hu J, and Pollack A. Identification of a single nucleotide polymorphism related to late toxicity in a randomized hypofractionation trial for prostate cancer. Annual meeting of American Society for Radiation Oncology, Miami, FL, 2011.

[7] Zuniga A, Thorstad W, Oh JH, Apte A, Bradley JD, and Deasy JO. Validating the use of a new tumor irradiation quality metric for lung and head and neck tumors: total clonogen survival. Annual Meeting of The American Association of Physicists in Medicine, Vancouver, Canada, 2011.

[6] Oh JH, Zuniga A, Thorstad W, Bradley JD, and Deasy JO. Tumor control probability models derived using machine learning for head and neck and lung tumors including a new metric, total clonogen survival (TCS). Annual Meeting of The American Association of Physicists in Medicine, Vancouver, Canada, 2011.

[5] Oh JH, Craft JM, Al-Lozi R, Vaidya M, Meng Y, Bradley JD, Deasy JO, and El Naqa I. Integrating dosimetry and biomarkers via a Bayesian network for predicting radiotherapy response in lung cancer. Annual Meeting of European Society for Therapeutic Radiology and Oncology, London, UK, 2011. 

[4] Craft JM, Oh JH, Ju M, Bradley JD, Deasy JO, and El Naqa I. Quantitative mass spectroscopy and the identification of Alpha2macroglobulin as a potential biomarker for radiation pneumonitis. Annual meeting of American Society for Radiation Oncology, San Diego, CA, 2010.

[3] Oh JH, Craft JM, Al-Lozi R, Meng Y, Deasy JO, Bradley JD, and El Naqa I. A Bayesian network approach for predicting local failure in lung cancer using physical and biological variables. Annual meeting of American Society for Radiation Oncology, San Diego, CA, 2010.

[2] Oh JH, Yang Y, and El Naqa I. A novel relevance feedback approach for efficient mammogram image retrieval. Annual Meeting of The American Association of Physicists in Medicine, Philadelphia, PA, 2010.

[1] Oh JH, Spencer S, Lichti C, Townsend R, Craft JM, Deasy JO, Bradley JD, and El Naqa I. Discovery of blood biomarkers for radiation pneumonitis by proteomics analysis. ASTRO Translational Advances in Radiation Oncology and Cancer Imaging Symposium, St. Louis, MO, 2009.