Patient classification based on pre-hospital heart rate variability. - Pavitra Padmanabhan; Zhiping Lin 001; Guang-Bin Huang; Marcus Eng Hock Ong (APCCAS, 2008)

Patient Outcome Prediction with Heart Rate Variability and Vital Signs. - Nan Liu 003; Zhiping Lin 001; Zhixiong Koh; Guang-Bin Huang; Wee Ser; Marcus Eng Hock Ong (J. Signal Process. Syst., 2011)

An Intelligent Scoring System and Its Application to Cardiac Arrest Prediction. - Nan Liu 003; Zhiping Lin 001; Jiuwen Cao; Zhixiong Koh; Tongtong Zhang; Guang-Bin Huang; Wee Ser; Marcus Eng Hock Ong (IEEE Trans. Inf. Technol. Biomed., 2012)

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection. - Nan Liu 003; Zhi Koh; Junyang Goh; Zhiping Lin 001; Benjamin Haaland; Boon Ting; Marcus Eng Hock Ong (BMC Medical Informatics Decis. Mak., 2014)

Risk Scoring for Prediction of Acute Cardiac Complications from Imbalanced Clinical Data. - Nan Liu 003; Zhixiong Koh; Eric Chern-Pin Chua; Licia Mei-Ling Tan; Zhiping Lin 001; Bilal Mirza; Marcus Eng Hock Ong (IEEE J. Biomed. Health Informatics, 2014)

Analysis of patient outcome using ECG and extreme learning machine ensemble. - Nan Liu 003; Jiuwen Cao; Zhixiong Koh; Zhiping Lin 001; Marcus Eng Hock Ong (DSP, 2015)

Effects of two new features of approximate entropy and sample entropy on cardiac arrest prediction. - Yumeng Gao; Zhiping Lin 001; Tongtong Zhang; Nan Liu 003; Tianchi Liu 001; Wee Ser; Zhixiong Koh; Marcus Eng Hock Ong (ISCAS, 2015)

Multi-objective optimization for a hospital inpatient flow process via discrete event simulation. - Yang Wang; Loo Hay Lee; Ek Peng Chew; Sean Shao Wei Lam; Seng Kee Low; Marcus Eng Hock Ong; Haobin Li (WSC, 2015)

Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients. - Tianchi Liu 001; Zhiping Lin 001; Marcus Eng Hock Ong; Zhixiong Koh; Pin Pin Pek; Yong Kiang Yeo; Beom-Seok Oh; Andrew Fu Wah Ho; Nan Liu 003 (Comput. Biol. Medicine, 2015)

Landmark recognition with sparse representation classification and extreme learning machine. - Jiuwen Cao; Yanfei Zhao; Xiaoping Lai; Marcus Eng Hock Ong; Chun Yin; Zhixiong Koh; Nan Liu 003 (J. Frankl. Inst., 2015)

A Feasible and Terrain-Insensitive Approach for Analyzing Power Wheelchair Users' Mobility. - Fang Li 010; Marcus Eng Hock Ong; Yan Daniel Zhao; Gang Qian; Jicheng Fu (ICTAI, 2017)

Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events. - Nan Liu 003; Jeffrey Tadashi Sakamoto; Jiuwen Cao; Zhixiong Koh; Andrew Fu Wah Ho; Zhiping Lin 001; Marcus Eng Hock Ong (Cogn. Comput., 2017)

Simulation-based decision support framework for dynamic ambulance redeployment in Singapore. - Sean Shao Wei Lam; Clarence Boon Liang Ng; Francis Ngoc Hoang Long Nguyen; Yih Yng Ng; Marcus Eng Hock Ong (Int. J. Medical Informatics, 2017)

FAM-FACE-SG: a score for risk stratification of frequent hospital admitters. - Lian Leng Low; Nan Liu 003; Kheng Hock Lee; Marcus Eng Hock Ong; Sijia Wang; Xuan Jing; Julian Thumboo (BMC Medical Informatics Decis. Mak., 2017)

Predictive Modeling of Hospital Readmissions with Sparse Bayesian Extreme Learning Machine. - Nan Liu 003; Lian Leng Low; Sean Shao Wei Lam; Julian Thumboo; Marcus Eng Hock Ong (ELM, 2018)

A Novel Approach for Assessing Power Wheelchair Users' Mobility by Using Curve Fitting. - Jicheng Fu; Fang Li 010; Marcus Eng Hock Ong; Tyler Cook; Gang Qian; Yan Daniel Zhao (HCI (17), 2018)

Serial Heart Rate Variability Measures for Risk Prediction of Septic Patients in the Emergency Department. - Calvin Chiew; Han Wang 001; Marcus Eng Hock Ong; Ting Hway Wong; Zhixiong Koh; Nan Liu 003; Mengling Feng (AMIA, 2019)

Explainable AI: Classification of MRI Brain Scans Orders for Quality Improvement. - Alwin Yaoxian Zhang; Sean Shao Wei Lam; Marcus Eng Hock Ong; Phua Hwee Tang; Ling Ling Chan (BDCAT, 2019)

A Novel Picture Fingerprinting Technique to Provide Practical Indoor Localization for Wheelchair Users. - Jicheng Fu; Paul Wiechmann; Marcus Eng Hock Ong; Gang Qian; Yan Daniel Zhao (HCI (34), 2019)

Risk-Based AED Placement - Singapore Case. - Ivan Derevitskii; Nikita Kogtikov; Michael Harold Lees; Wentong Cai 001; Marcus Eng Hock Ong (ICCS (4), 2020)

Modeling Helping Behavior in Emergency Evacuations Using Volunteer's Dilemma Game. - Jaeyoung Kwak; Michael Harold Lees; Wentong Cai 001; Marcus Eng Hock Ong (ICCS (1), 2020)

Prediction of ROSC After Cardiac Arrest Using Machine Learning. - Nan Liu 003; Andrew Fu Wah Ho; Pin Pin Pek; Tsung-Chien Lu; Pairoj Khruekarnchana; Kyoung Jun Song; Hideharu Tanaka; Ghulam Yasin Naroo; Han Nee Gan; Zhixiong Koh; Huei-Ming Ma; Marcus Eng Hock Ong (MIE, 2020)

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)

Recurrent Temporal Point Process Network for First and Repeated Clinical Events. - Min Min Chan; Amanda Yun Rui Lam; David Carmody; Marcus Eng Hock Ong; Yingtian Zou; Wynne Hsu; Mong-Li Lee (ICTAI, 2021)

A Model-based Analysis of Evacuation Strategies in Hospital Emergency Departments. - Boyi Su; Jaeyoung Kwak; Ahmadreza Pourghaderi; Michael Harold Lees; Kenneth B. K. Tan; Shin Yi Loo; Ivan S. Y. Chua; Joy L. J. Quah; Wentong Cai 001; Marcus Eng Hock Ong (WSC, 2021)

Shapley variable importance clouds for interpretable machine learning. - Yilin Ning; Marcus Eng Hock Ong; Bibhas Chakraborty; Benjamin Alan Goldstein; Daniel Shu Wei Ting; Roger Vaughan; Nan Liu 003 (CoRR, 2021)

HRnV-Calc: A software package for heart rate n-variability and heart rate variability analysis. - Chenglin Niu; Dagang Guo; Marcus Eng Hock Ong; Zhixiong Koh; Andrew Fu Wah Ho; Zhiping Lin 001; Chengyu Liu 001; Gari D. Clifford; Nan Liu 003 (CoRR, 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)

Simulation-Based Analysis of Evacuation Elevator Allocation for a Multi-Level Hospital Emergency Department. - Boyi Su; Jaeyoung Kwak; Ahmad Reza Pourghaderi; Michael Harold Lees; Kenneth B. K. Tan; Shin Yi Loo; Ivan S. Y. Chua; Joy L. J. Quah; Wentong Cai 001; Marcus Eng Hock Ong (WSC, 2022)

Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making. - Mingxuan Liu; Yilin Ning; Han Yuan; Marcus Eng Hock Ong; Nan Liu 003 (CoRR, 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)

Resuming elective surgery after COVID-19: A simulation modelling framework for guiding the phased opening of operating rooms. - Hairil Rizal Abdullah; Sean Shao Wei Lam; Boon Yew Ang; Ahmadreza Pourghaderi; Francis Ngoc Hoang Long Nguyen; David Bruce Matchar; Hiang Khoon Tan; Marcus Eng Hock Ong (Int. J. Medical Informatics, 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)

Shapley variable importance cloud for interpretable machine learning. - Yilin Ning; Marcus Eng Hock Ong; Bibhas Chakraborty; Benjamin Alan Goldstein; Daniel Shu Wei Ting; Roger Vaughan; Nan Liu 003 (Patterns, 2022)

A roadmap to fair and trustworthy prediction model validation in healthcare. - Yilin Ning; Victor Volovici; Marcus Eng Hock Ong; Benjamin Alan Goldstein; Nan Liu 003 (CoRR, 2023)

Towards clinical AI fairness: A translational perspective. - Mingxuan Liu; Yilin Ning; Salinelat Teixayavong; Mayli Mertens; Jie Xu 012; Daniel Shu Wei Ting; Lionel Tim-Ee Cheng; Jasmine Chiat Ling Ong; Zhen Ling Teo; Ting Fang Tan; Ravi Chandran Narrendar; Fei Wang 001; et al. (CoRR, 2023)

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)

A translational perspective towards clinical AI fairness. - Mingxuan Liu; Yilin Ning; Salinelat Teixayavong; Mayli Mertens; Jie Xu 012; Daniel Shu Wei Ting; Lionel Tim-Ee Cheng; Jasmine Chiat Ling Ong; Zhen Ling Teo; Ting Fang Tan; Ravi Chandran Narrendar; Fei Wang 001; et al. (npj Digit. Medicine, 2023)

Viewing the Role of Alternate Care Service Pathways in the Emergency Care System through a Causal Loop Diagram Lens. - Ashish Kumar; Zhenghong Liu; John Pastor Ansah; Yih Yng Ng; Benjamin Sieu-Hon Leong; David Bruce Matchar; Marcus Eng Hock Ong; Fahad Javaid Siddiqui (Syst., 2023)

HRnV-Calc: A Software for Heart Rate n-Variability and Heart Rate Variability Analysis. - Chenglin Niu; Dagang Guo; Marcus Eng Hock Ong; Zhixiong Koh; Guerry Alexiane Laure Marie-Alix; Andrew Fu Wah Ho; Zhiping Lin 001; Chengyu Liu 001; Gari D. Clifford; Nan Liu 003 (J. Open Source Softw., 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)

Simulation of Emergency Care Systems: A Taxonomy and Future Directions. - Sean Shao Wei Lam; Ashish Kumar; Guo Yuan; Michael Dorosan; Marcus Eng Hock Ong; Fahad Javaid Siddiqui (WSC, 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)

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)

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)

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)

Deep learning modelling to forecast emergency department visits using calendar, meteorological, internet search data and stock market price. - Chua Ming; Geraldine Jw Lee; Yao Neng Teo; Yao Hao Teo; Xinyan Zhou; Elizabeth Sy Ho; Emma Ms Toh; Marcus Eng Hock Ong; Benjamin Yq Tan; Andrew Fw Ho (Comput. Methods Programs Biomed., 2025)

Optimising design of clinical decision support systems and implementation strategies to improve radiological imaging appropriateness - A qualitative study in the emergency department. - Yi Xiang Tay; Jeremy C. P. Wee; Marcus Eng Hock Ong; Shane J. Foley; Robert Chun Chen; Lai Peng Chan; Ronan Killeen; Ivan S. Y. Chua; Jonathan P. McNulty (Int. J. Medical Informatics, 2025)

Clinical and economic impact of a large language model in perioperative medicine: a randomized crossover trial. - Yuhe Ke; Bernard Soon Yang Ong; Liyuan Jin; Jacqueline Sim; Chi Ho Chan; Chai Rick Soh; Danny Jon Nian Wong; Nan Liu 003; Ban Leong Sng; Daniel Shu Wei Ting; Su Qian Yeo; Marcus Eng Hock Ong; et al. (npj Digit. Medicine, 2025)

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)