Development and Validation of a Survival Score for the Emergency Department in Singapore. - Feng Xie 004; Bibhas Chakraborty; Nan Liu 003; Marcus Eng Hock Ong (AMIA, 2021)

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)

AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes. - Seyed Ehsan Saffari; Yilin Ning; Feng Xie 004; Bibhas Chakraborty; Victor Volovici; Roger Vaughan; Marcus Eng Hock Ong; 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)

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. - Feng Xie 004; Yilin Ning; Han Yuan; Benjamin Alan Goldstein; Marcus Eng Hock Ong; Nan Liu 003; Bibhas Chakraborty (J. Biomed. Informatics, 2022)

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. - Feng Xie 004; Han Yuan; Yilin Ning; Marcus Eng Hock Ong; Mengling Feng; Wynne Hsu; Bibhas Chakraborty; Nan Liu 003 (J. Biomed. Informatics, 2022)

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. - Han Yuan; Feng Xie 004; Marcus Eng Hock Ong; Yilin Ning; Marcel Lucas Chee; Seyed Ehsan Saffari; Hairil Rizal Abdullah; Benjamin Alan Goldstein; Bibhas Chakraborty; Nan Liu 003 (J. Biomed. Informatics, 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)

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)

Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models. - David Seong; Samson Mataraso; Camilo Espinosa; Eloïse Berson; S. Momsen Reincke; Lei Xue; Chloe Kashiwagi; Yeasul Kim; Chi-Hung Shu; Philip Chung 005; Marc Ghanem; Feng Xie 004; et al. (Briefings Bioinform., 2024)

Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission. - Ziwen Wang; Jin Wee Lee; Tanujit Chakraborty; Yilin Ning; Mingxuan Liu; Feng Xie 004; Marcus Eng Hock Ong; Nan Liu 003 (CoRR, 2024)