Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records. - Feng Xie 004; Jun Zhou 014; Jin Wee Lee; Mingrui Tan; Siqi Li 004; Logasan S/O Rajnthern; Marcel Lucas Chee; Bibhas Chakraborty; An-Kwok Ian Wong; Alon Dagan; Marcus Eng Hock Ong; Fei Gao; et al. (CoRR, 2021)

A Novel Interpretable Machine Learning System to Generate Clinical Risk Scores: An Application for Predicting Early Mortality or Unplanned Readmission in A Retrospective Cohort Study. - Yilin Ning; Siqi Li 004; Marcus Eng Hock Ong; Feng Xie 004; Bibhas Chakraborty; Daniel Shu Wei Ting; Nan Liu 003 (AMIA, 2022)

Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records. - Feng Xie 004; Jun Zhou 014; Jin Wee Lee; Mingrui Tan; Siqi Li 004; Logasan S/O Rajnthern; Marcel Lucas Chee; Bibhas Chakraborty; An-Kwok Ian Wong; Alon Dagan; Marcus Eng Hock Ong; Fei Gao; et al. (AMIA, 2022)

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; Victor Volovici; Bibhas Chakraborty; Nan Liu 003 (CoRR, 2022)

Interpretable Machine Learning-Based Risk Scoring with Individual and Ensemble Model Selection for Clinical Decision Making. - Han Yuan; Jin Wee Lee; Mingxuan Liu; Siqi Li 004; Chenglin Niu; Jun Wen; Feng Xie 004 (Tiny Papers @ ICLR, 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)

FedScore: A privacy-preserving framework for federated scoring system development. - Siqi Li 004; Yilin Ning; Marcus Eng Hock Ong; Bibhas Chakraborty; Chuan Hong; Feng Xie 004; Han Yuan; Mingxuan Liu; Daniel M. Buckland; Yong Chen 016; Nan Liu 003 (J. Biomed. Informatics, 2023)

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. - Siqi Li 004; Pinyan Liu; Gustavo G. Nascimento; Xinru Wang; Fabio Renato Manzolli Leite; Bibhas Chakraborty; Chuan Hong; Yilin Ning; Feng Xie 004; Zhen Ling Teo; Daniel Shu Wei Ting; Hamed Haddadi; et al. (J. Am. Medical Informatics Assoc., 2023)

Transfer Learning for Global Feature Importance Measurements. - Xin Li 079; Siqi Li 004; Qiming Wu 001; Kunyu Yu (Tiny Papers @ ICLR, 2024)

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)

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)

FedIMPUTE: Privacy-preserving missing value imputation for multi-site heterogeneous electronic health records. - Siqi Li 004; Mengying Yan; Ruizhi Yuan; Molei Liu; Nan Liu 003; Chuan Hong (J. Biomed. Informatics, 2025)

SIM-Shapley: A Stable and Computationally Efficient Approach to Shapley Value Approximation. - Wangxuan Fan; Siqi Li 004; Doudou Zhou; Yohei Okada; Chuan Hong; Molei Liu; Nan Liu 003 (CoRR, 2025)

Benchmarking Foundation Models with Multimodal Public Electronic Health Records. - Kunyu Yu; Rui Yang 016; Jingchi Liao; Siqi Li 004; Huitao Li; Irene Li; Yifan Peng; Rishikesan Kamaleswaran; Nan Liu 003 (CoRR, 2025)