| Benchmarking emergency department prediction models with machine learning and public electronic health records F Xie, J Zhou, JW Lee, M Tan, S Li, LSO Rajnthern, ML Chee, ... Scientific Data 9 (1), 658, 2022 | 23 | 2022 |
| Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques M Liu*, S Li*, H Yuan, MEH Ong, Y Ning, F Xie, SE Saffari, Y Shang, ... Artificial Intelligence in Medicine, 102587, 2023 | 19 | 2023 |
| A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort … Y Ning, S Li, MEH Ong, F Xie, B Chakraborty, DSW Ting, N Liu PLOS Digital Health 1 (6), e0000062, 2022 | 14 | 2022 |
| Federated and distributed learning applications for electronic health records and structured medical data: A scoping review S Li, P Liu, GG Nascimento, X Wang, FRM Leite, B Chakraborty, C Hong, ... Journal of the American Medical Informatics Association 30 (12), 2041–2049, 2023 | 7 | 2023 |
| Development and validation of an interpretable clinical score for early identification of acute kidney injury at the emergency department Y Ang*, S Li*, MEH Ong, F Xie, SH Teo, L Choong, R Koniman, ... Scientific Reports 12 (1), 7111, 2022 | 5 | 2022 |
| FedScore: A privacy-preserving framework for federated scoring system development S Li, Y Ning, MEH Ong, B Chakraborty, C Hong, F Xie, H Yuan, M Liu, ... Journal of Biomedical Informatics 146 (104485), 2023 | 4 | 2023 |
| Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture ZL Teo, L Jin, S Li, D Miao, X Zhang, WY Ng, TF Tan, DM Lee, KJ Chua, ... Cell Reports Medicine, 2024 | 2 | 2024 |
| A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes F Xie, Y Ning, M Liu, S Li, SE Saffari, H Yuan, V Volovici, DSW Ting, ... STAR protocols 4 (2), 102302, 2023 | 1 | 2023 |
| Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data S Li, Y Shang, Z Wang, Q Wu, C Hong, Y Ning, D Miao, MEH Ong, ... arXiv preprint arXiv:2403.05229, 2024 | | 2024 |
| CanVaxKB: a web-based cancer vaccine knowledgebase E Asfaw, AY Lin, A Huffman, S Li, M George, C Darancou, M Kalter, ... NAR cancer 6 (1), zcad060, 2024 | | 2024 |
| Federation of scoring systems EHMO Nan Liu, Siqi Li WO Patent 2024039301A1, 2024 | | 2024 |
| Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches S Li, D Miao, Q Wu, C Hong, D D'Agostino, X Li, Y Ning, Y Shang, H Fu, ... arXiv preprint arXiv:2311.03417, 2023 | | 2023 |
| Interpretable Machine Learning-Based Risk Scoring with Individual and Ensemble Model Selection for Clinical Decision Making H Yuan, J Lee, M Liu, S Li, C Niu, J Wen, F Xie | | 2023 |
| Robust and Interpretable Machine Learning Assessment of Variable Importance with Moderate to Small Sample Sizes: A Study of Survival after Out-Of-Hospital Cardiac Arrest Y Ning, S Li, YY Ng, MYC Chia, HN Gan, L Tiah, DRH Mao, WM Ng, ... Available at SSRN 4423470, 2023 | | 2023 |
| Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records Q Wu, S Li, D Miao, Y Shang, X Li, N Liu The Second Tiny Papers Track at ICLR 2024, 0 | | |
| Empirical Evaluations of Personalized Federated Learning on Heterogeneous Electronic Health Records Y Shang, Q Wu, S Li, D Miao The Second Tiny Papers Track at ICLR 2024, 0 | | |
| Transfer Learning for Global Feature Importance Measurements X Li, S Li, Q Wu, K Yu The Second Tiny Papers Track at ICLR 2024, 0 | | |
MEH ONGSenior Consultant, Singapore General HospitalVerified email at sgh.com.sg
