Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist. - Yilin Ning; Salinelat Teixayavong; Yuqing Shang; Julian Savulescu; Vaishaanth Nagaraj; Di Miao; Mayli Mertens; Daniel Shu Wei Ting; Jasmine Chiat Ling Ong; Mingxuan Liu; Jiuwen Cao; Michael Dunn; et al. (CoRR, 2023)

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches. - Siqi Li 004; Di Miao; Qiming Wu 001; Chuan Hong; Danny D'Agostino; Xin Li 079; Yilin Ning; Yuqing Shang; Huazhu Fu; Marcus Eng Hock Ong; Hamed Haddadi; Nan Liu 003 (CoRR, 2023)

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. - Mingxuan Liu; Siqi Li 004; Han Yuan; Marcus Eng Hock Ong; Yilin Ning; Feng Xie 004; Seyed Ehsan Saffari; Yuqing Shang; Victor Volovici; Bibhas Chakraborty; Nan Liu 003 (Artif. Intell. Medicine, 2023)

Empirical Evaluations of Personalized Federated Learning on Heterogeneous Electronic Health Records. - Yuqing Shang; Qiming Wu 001; Siqi Li 004; Di Miao (Tiny Papers @ ICLR, 2024)

Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records. - Qiming Wu 001; Siqi Li 004; Di Miao; Yuqing Shang; Xin Li 079; Nan Liu 003 (Tiny Papers @ ICLR, 2024)

Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data. - Siqi Li 004; Yuqing Shang; Ziwen Wang; Qiming Wu 001; Chuan Hong; Yilin Ning; Di Miao; Marcus Eng Hock Ong; Bibhas Chakraborty; Nan Liu 003 (CoRR, 2024)

Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare. - Mingxuan Liu; Yilin Ning; Yuhe Ke; Yuqing Shang; Bibhas Chakraborty; Marcus Eng Hock Ong; Roger Vaughan; Nan Liu 003 (CoRR, 2024)

Towards Clinical AI Fairness: Filling Gaps in the Puzzle. - Mingxuan Liu; Yilin Ning; Salinelat Teixayavong; Xiaoxuan Liu; Mayli Mertens; Yuqing Shang; Xin Li 079; Di Miao; Jie Xu 012; Daniel Shu Wei Ting; Lionel Tim-Ee Cheng; Jasmine Chiat Ling Ong; et al. (CoRR, 2024)

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis. - Siqi Li 004; Xin Li 079; Kunyu Yu; Di Miao; Mingcheng Zhu 003; Mengying Yan; Yuhe Ke; Danny D'Agostino; Yilin Ning; Qiming Wu 001; Ziwen Wang; Yuqing Shang; et al. (CoRR, 2024)

FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction. - Siqi Li 004; Qiming Wu 001; Xin Li 079; Di Miao; Chuan Hong; Wenjun Gu; Yuqing Shang; Yohei Okada; Michael Hao Chen; Mengying Yan; Yilin Ning; Marcus Eng Hock Ong; et al. (CoRR, 2024)

FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare. - Mingxuan Liu; Yilin Ning; Yuhe Ke; Yuqing Shang; Bibhas Chakraborty; Marcus Eng Hock Ong; Roger Vaughan; Nan Liu 003 (Patterns, 2024)

A scoping review and evidence gap analysis of clinical AI fairness. - Mingxuan Liu; Yilin Ning; Salinelat Teixayavong; Xiaoxuan Liu; Mayli Mertens; Yuqing Shang; Xin Li 079; Di Miao; Jingchi Liao; Jie Xu 012; Daniel Shu Wei Ting; Lionel Tim-Ee Cheng; et al. (npj Digit. Medicine, 2025)