Learning and Estimation of Single Molecule Behavior. - Sivaraman Rajaganapathy; James Melbourne; Tanuj Aggarwal; Rachit Shrivastava; Murti V. Salapaka (ACC, 2018)

Change detection using an iterative algorithm with guarantees. - Sivaraman Rajaganapathy; James Melbourne; Murti V. Salapaka (Autom., 2022)

Learning Physician's Treatment for Alzheimer's Disease based on Electronic Health Records and Reinforcement Learning. - Kritib Bhattarai; Sivaraman Rajaganapathy; Trisha Das; Yejin Kim 001; Yongbin Chen; Qiying Dai; Xiaoyang Li; Xiaoqian Jiang; Nansu Zong (ICHI, 2023)

Evaluation of GPT-3 for Anti-Cancer Drug Sensitivity Prediction. - Shaika Chowdhury; Sivaraman Rajaganapathy; Lichao Sun; James R. Cerhan; Nansu Zong (CoRR, 2023)

Using artificial intelligence to learn optimal regimen plan for Alzheimer's disease. - Kritib Bhattarai; Sivaraman Rajaganapathy; Trisha Das; Yejin Kim 001; Yongbin Chen; Qiying Dai; Xiaoyang Li; Xiaoqian Jiang; Nansu Zong (J. Am. Medical Informatics Assoc., 2023)

Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction. - Shaika Chowdhury; Yongbin Chen; Pengyang Li; Sivaraman Rajaganapathy; Andrew Wen; Xiao Ma 019; Qiying Dai; Yue Yu; Sunyang Fu; Xiaoqian Jiang; Zhe He 001; Sunghwan Sohn; et al. (J. Am. Medical Informatics Assoc., 2024)

Advancing efficacy prediction for electronic health records based emulated trials in repurposing heart failure therapies. - Nansu Zong; Shaika Chowdhury; Shibo Zhou; Sivaraman Rajaganapathy; Yue Yu; Liewei Wang; Qiying Dai; Pengyang Li; Xiaoke Liu; Suzette J. Bielinski; Jun Chen; Yongbin Chen; et al. (npj Digit. Medicine, 2025)

Launching Insights: A Pilot Study on Leveraging Real-World Observational Data from the Mayo Clinic Platform to Advance Clinical Research. - Yue Yu; Xinyue Hu; Sivaraman Rajaganapathy; Jingna Feng; Ahmed Abdelhameed; Xiaodi Li; Jianfu Li; Ken Liu; Liu Yang; Nilufer Taner; Phil Fiero; Soulmaz Boroumand; et al. (CoRR, 2025)