In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare. - Mustafa Y. Topaloglu; Elisabeth M. Morrell; Suraj Rajendran; Umit Topaloglu (Frontiers Artif. Intell., 2021)

Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources. - Suraj Rajendran; Weishen Pan; Mert R. Sabuncu; Yong Chen 016; Jiayu Zhou; Fei Wang 001 (CoRR, 2023)

Applications of machine Learning to improve the efficiency and range of microbial biosynthesis: a review of state-of-art techniques. - Akshay Bhalla; Suraj Rajendran (CoRR, 2023)

Nanorobotics in Medicine: A Systematic Review of Advances, Challenges, and Future Prospects. - Shishir Rajendran; Prathic Sundararajan; Ashi Awasthi; Suraj Rajendran (CoRR, 2023)

Advancing Melanoma Diagnosis with Self-Supervised Neural Networks: Evaluating the Effectiveness of Different Techniques. - Srivishnu Vusirikala; Suraj Rajendran (CoRR, 2024)

Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation. - Suraj Rajendran; Weishen Pan; Mert R. Sabuncu; Yong Chen 016; Jiayu Zhou; Fei Wang 001 (Patterns, 2024)

An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals. - Weishen Pan; Zhenxing Xu; Suraj Rajendran; Fei Wang 001 (Patterns, 2024)

Federated target trial emulation using distributed observational data for treatment effect estimation. - Haoyang Li 001; Chengxi Zang; Zhenxing Xu; Weishen Pan; Suraj Rajendran; Yong Chen 016; Fei Wang 001 (npj Digit. Medicine, 2025)

TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials. - Rui Sheng; Xingbo Wang 001; Jiachen Wang; Xiaofu Jin; Zhonghua Sheng; Zhenxing Xu; Suraj Rajendran; Huamin Qu; Fei Wang 001 (CoRR, 2025)