KS Shehadeh, MY Tsang, R Padman, A Kilic. 2025, Operating Room-to-Downstream Elective Surgery Planning Under Uncertainty. European Journal of Operational Research, In Press.
R. Padman, KS Shehadeh, A Mohanan, A Kilic. 2025. Analyzing Hospital Readmission after Transcatheter Aortic Valve Replacement (TAVR). Book Chapter, In New Technologies, Precision Medicine, and AI Emergency General Surgery, B. de Simone (Ed.), Springer Book.
Y. Li, X. Yao, R. Padman. 2025. No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Networks. AMIA Annu Symp Proc. 2025.
Y Luo, R Skandari, C Martinez, A Kilic, R Padman. 2025. Benchmarking Waitlist Mortality Prediction Through Time-to-Event Modeling using New UNOS Dataset. AMIA Annu Symp Proc. 2025.
KS Shehadeh, R. Padman. 2025. Machine Learning and Optimization for Comprehensive Upstream-to-Downstream Surgical Scheduling and Capacity Planning. Chapter 13, Artificial Intelligence and Machine Learning in Healthcare, First Edition (A. Kilic, Editor), Elsevier.
Y Li, Y Miao, X Ding, R Krishnan, R Padman. 2025. Firm or Fickle? Evaluating Large Language Models Consistency in Sequential Interactions. In Findings of the Association for Computational Linguistics: ACL 2025, pages 6679–6700, Vienna, Austria. Association for Computational Linguistics.
X Liu, A Susarla, R Padman. 2025. Promoting Health Literacy With Human-in-the-Loop Video Understandability Classification of YouTube Videos: Development and Evaluation Study. Journal of Medical Internet Research (JMIR). 2025;27:e56080, doi: 10.2196/56080
R Padman, R Ladhania. 2024. Artificial Intelligence and Gamification for Health. Book Chapter, In "Transformative Artificial Intelligence: Advances for Ecology, Health and Education", M Pagani (Ed.), Edward Elgar Publishing, 2024.
K Pothugunta, X Liu, A Susarla, R Padman. 2024. Classifying Actionable Information in Videos using HST-CAT: Hybrid Spatiotemporal Cross - Attention Transformer. ICIS 2024 Proceedings.
Li Y, Al-Sayouri S, Padman R. Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques. AMIA Annu Symp Proc. 2025 May 22;2024:664-673. PMID: 40417492; PMCID: PMC12099416.
J Bian, N Liu, SM Overgaard, R Padman, PAD Steel, V Tiase, CA Whitcomb, J Zhang, Y Zhang. 2024. Transdisciplinary Perspectives for Health Systems Science. npj Health Systems Editorial - September 2024.
K Pothugunta, X Liu, A Susarla, R Padman. 2024. Assessing Inclusion and Representativeness on Digital Platforms for Health Literacy: Evidence from YouTube. J Biomed Informatics 2024, Sep:157:104669. doi: 10.1016/j.jbi.2024.104669. Epub 2024 Jun 15.
X Yao, KS Shehadeh, R Padman. 2024. Multi-Resource Allocation and Care Sequence Assignment in Patient Management: A Stochastic Programming Approach. Health Care Management Science. 980692 27, 352–369 (2024).
O Ben-Assuli, T Heart, N Yin, R. Klempfner, R Padman. 2024. On Expert-Machine Partnership to Predict Mortality of Congestive Heart Failure Patients. Information Systems Management. https://doi.org/10.1080/10580530.2024.2312380.
M. Chen, X. Tan, R. Padman. 2023. A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study. J Med Internet Res., 2023 Jan 30;25:e36477. doi: 10.2196/36477.
Burstin, H., S. Curry, M. Ranney, V. Arora, B. Boxer Wachler, W.-Y. S. Chou, R. Correa, D. Cryer, D. Dizon, E. Flores, G. Harmon, A. Jain, K. Johnson, C. Laine, L. Leininger, G. McMahon, L. Michaelis, R. Minhas, R. Mularski, J. Oldham, R. Padman, C. Pinnock, J. Rivera, B. Southwell, A. Villarruel, and K. Wallace. 2023. Identifying Credible Sources of Health Information in Social Media: Phase 2—Considerations for Non-accredited Nonprofit Organizations, For-profit Entities, and Individual Sources. NAM Perspectives. Discussion Paper, National Academy of Medicine, Washington, DC.
G Shmueli, B Colosimo, D Martens, R Padman, M Saar-Tsechansky, O Sheng, WN Street, and K Tsui. 2023. How can IJDS authors, reviewers, and editors use (and misuse) generative AI?. IJDS Editorial, Issue #3 (June 2023).
O Ben-Assuli, T Heart, R. Klempfner, R Padman. 2023. Human-machine collaboration for feature selection and integration to improve congestive Heart failure risk prediction. Decision Support Systems, Vol. 172, 2023, 113982, ISSN 0167-9236, https://doi.org/10.1016/j.dss.2023.113982.
S Kumar, M Arnold, G James, R Padman. 2022. Developing a common data model approach for DISCOVER CKD: A retrospective, global cohort of real-world patients with chronic kidney disease. PLoS ONE 17(9): e0274131. https://doi.org/10.1371/journal.pone.0274131.
Reamer C, Chi WN, Gordon R, Sarswat N, Gupta C, Gaznabi S, White VanGompel E, Szum I, Morton-Jost M, Vaughn J, Larimer K, Victorson D, Erwin J, Halasyamani L, Solomonides A, Padman R, Shah NS. Continuous Remote Patient Monitoring in Patients With Heart Failure (Cascade Study): Protocol for a Mixed Methods Feasibility Study. JMIR Res Protoc. 2022 Aug 25;11(8):e36741. doi: 10.2196/36741.
N. Khera, N. Zhang, T. Hilal, U. Durani, M. Lee, R. Padman, S. Voleti, R.M. Warsame, B. Borah, K. R. Yabroff, J. M. Griffin. 2022. Association of Health Insurance Literacy with Financial Hardship in Patients with Cancer. JAMA Network Open.2022;5(7):e2223141. doi:10.1001/jamanetworkopen. 2022.23141.
K. Shehadeh, R. Padman. 2022. Stochastic Optimization Approaches for Elective Surgery Scheduling and Downstream Capacity Planning: Models, Challenges, and Opportunities. Computers and Operations Research, 137 (2022) 105523.
WN Chi, C Reamer, R Gordon, N Sarswat, C Gupta, EW VanGompel, J Dayiantis, M Morton-Jost, K Larimer, DE Victorson, L Halasyamani, A Solomonides, R Padman, NS Shah. 2021. Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch. Applied Clinical Informatics, 2021;12:1161–1173.
F. Movahedi, R. Padman, J. Antaki. 2021. Limitations of receiver operating characteristic curve on imbalanced data: Assist device mortality risk scores. Journal of Thoracic and Cardiovascular Surgery, Volume 165, Issue 4, Pages 1433-1442.e2. doi.org/10.1016/j.jtcvs.2021.07.041
Kilic A, Dochtermann D, Padman R, Miller JK, Dubrawski A (2021). Using machine learning to improve risk prediction in durable left ventricular assist devices. PLOS ONE 16(3): e0247866. https://doi.org/10.1371/journal.pone.0247866.
K. Shehadeh, R. Padman (2021). A Distributionally Robust Optimization Approach for Stochastic Elective Surgery Scheduling with Limited Intensive Care Unit Capacity. European Journal of Operational Research. Volume 290, Issue 3, 2021, Pages 901-913, ISSN 0377-2217, https://doi.org/10.1016/j.ejor.2020.09.001.
Kato-Lin Y, Kumar UB, Sri Prakash B, Prakash B, Varadan V, Agnihotri S, Subramanyam N, Krishnatray P, Padman R (2020). Impact of Pediatric Mobile Game Play on Healthy Eating Behavior: Randomized Controlled Trial. JMIR Mhealth Uhealth 2020;8(11):e15717 doi: 10.2196/15717.
Kilic A, Macickova J, Duan L, Movahedi F, Seese L, Zhang Y, Jacoski MV, Padman R. Machine Learning Approaches to Analyzing Adverse Events Following Durable LVAD Implantation (2020). Annals of Thoracic Surgery (accepted, in press).
M. Chen, X. Tan, R. Padman (2020). Social Determinants of Health in Electronic Health Records and Their Impact on Analysis and Risk Prediction: A Systematic Review. Journal of the American Medical Informatics Association, Volume 27, Issue 11, pp. 1764-1773, https://doi.org/10.1093/jamia/ocaa143.
R. Kamaleswaran, J. Lian, D. Lin, H. Molakapuri, S. Nunna, P. Shah, S. Dua, R. Padman (2020). Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms. AMIA Annu Symp Proc. 2020.
W. Wang, H. Zhao, H. Zuang, N. Shah, R. Padman (2020). DyCRS: Dynamic Interpretable Postoperative Complication Risk Scoring. WWW’20: Proceedings of the Web Conference 2020, Taipei, Taiwan, https://doi.org/10.1145/3366423.3380253.
X. Liu, A. Susarla, B. Zhang, R. Padman (2020). Go To YouTube and Call Me in the Morning: Use of Social Media for Chronic Conditions. Special Issue of MIS Quarterly on “The Role of Information Systems and Analytics in Chronic Disease Prevention and Management”, 257-283; DOI: 10.25300/MISQ/2020/15107.
O. Ben-Assuli, R. Padman (2020). Trajectories of Repeated Readmissions of Chronic Disease Patients: Risk Stratification, Profiling, and Predictions. Special Issue of MIS Quarterly on “The Role of Information Systems and Analytics in Chronic Disease Prevention and Management”, 201-226; DOI: 10.25300/MISQ/2020/15101.
F. Movahedi, R. L. Kormos, L. Lohmueller, L. Seese, M. Kanwar, S. Murali, Y. Zhang, R. Padman, J. F. Antaki (2019). Sequential Pattern Mining of Longitudinal Adverse Events After Left Ventricular Assist Device Implant. IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/jbhi.2019.2958714.
D. Gartner, R. Padman (2019). Flexible Hospital-wide Elective Patient Scheduling. Journal of the Operational Research Society (JORS). DOI: 10.1080/01605682.2019.1590509.
Y.C Lin, R. Padman (2019). RFID Technology-Enabled Markov Reward Process for Sequencing Care Coordination in Ambulatory Care: A Case Study. International Journal of Information Management, Volume 48, Pages 12-2. https://doi.org/10.1016/j.ijinfomgt.2019.01.018.
D. Gartner, R. Padman (2019). Machine Learning for Behavioral Healthcare Analytics: Addressing Waiting Time Perceptions in Emergency Care. Journal of the Operational Research Society Special Issue on Healthcare Behavioural OR, 1-14.
L. Seese, F. Movahedi, J. Antaki, R. Padman (2019). Delineating Pathways to Death by Multisystem Organ Failure in Patients with a Left Ventricular Assist Device (LVAD). The Journal of Heart and Lung Transplantation 38(4):S354; DOI: 10.1016/j.healun.2019.01.900.
O. Ben-Assuli, R. Padman, I. Shabtai (2019). Exploring Trajectories of Frequent Emergency Department Visits using a Laboratory-based Indicator of Serious Illness. Healthcare Informatics Journal. 22:1460458218824751. doi: 10.1177/1460458218824751.
H. Hao, R. Padman, B. Sun, R. Telang (2018). Quantifying the Impact of Social Learning on Information Technology Adoption: A Hierarchical Bayesian Learning Approach. Information Systems Research, 29 (1): 25-41.