Coronavirus disease 2019 (COVID-19): an evidence map of medical literature LIU NAN, ML Chee, C Niu, PP Pek, FJ Siddiqui, JP Ansah, DB Matchar, ... Springer Nature, 2020 | 84* | 2020 |
Leveraging Machine Learning Techniques and Engineering of Multi-Nature Features for National Daily Regional Ambulance Demand Prediction AX Lin, AFW Ho, KH Cheong, Z Li, W Cai, ML Chee, YY Ng, X Xiao, ... International Journal of Environmental Research and Public Health 17 (11), 4179, 2020 | 38 | 2020 |
Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review ML Chee, MEH Ong, FJ Siddiqui, Z Zhang, SL Lim, AFW Ho, N Liu International Journal of Environmental Research and Public Health 18 (9), 4749, 2021 | 30 | 2021 |
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 | 21 | 2022 |
Heart rate n-variability (HRnV) measures for prediction of mortality in sepsis patients presenting at the emergency department N Liu, ML Chee, MZQ Foo, JZ Pong, D Guo, ZX Koh, AFW Ho, C Niu, ... Plos one 16 (8), e0249868, 2021 | 16 | 2021 |
Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department N Liu, ML Chee, ZX Koh, SL Leow, AFW Ho, D Guo, MEH Ong BMC medical research methodology 21, 1-13, 2021 | 13 | 2021 |
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data H Yuan, F Xie, MEH Ong, Y Ning, ML Chee, SE Saffari, HR Abdullah, ... Journal of Biomedical Informatics 129, 104072, 2022 | 12 | 2022 |
Artificial Intelligence and Machine Learning in Prehospital Emergency Care: A Scoping Review ML Chee, ML Chee, H Huang, K Mazzochi, K Taylor, H Wang, M Feng, ... iScience, 2023 | 3 | 2023 |
Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records F Xie, J Zhou, JW Lee, M Tan, S Li, LS Rajnthern, ML Chee, ... | 1 | 2021 |
Artificial Intelligence and Machine Learning in Prehospital Emergency Care: A Systematic Scoping Review ML Chee, ML Chee, H Huang, K Mazzochi, K Taylor, H Wang, M Feng, ... medRxiv, 2023.04. 25.23289087, 2023 | | 2023 |
Benchmarking emergency department triage prediction models with machine learning and large public electronic health records F Xie, J Zhou, JW Lee, M Tan, S Li, LS Rajnthern, ML Chee, ... arXiv preprint arXiv:2111.11017, 2021 | | 2021 |
Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review (preprint) ML Chee, MEH Ong, FJ Siddiqui, Z Zhang, SL Lim, AFW Ho, N Liu | | 2021 |
Machine learning dimensionality reduction showed marginal performance benefit over stepwise regression for risk stratification of chest pain patients in the emergency department N Liu, ML Chee, ZX Koh, SL Leow, AFW Ho, D Guo, MEH Ong | | 2020 |
Machine learning dimensionality reduction for heart rate n-variability (HRnV) based risk stratification of chest pain patients in the emergency department N Liu, ML Chee, ZX Koh, SL Leow, AF Wah Ho, D Guo, ME Hock Ong medRxiv, 2020.07. 05.20146571, 2020 | | 2020 |
Coronavirus Disease 2019 (COVID-19): An Evidence Map of Medical Literature (preprint) N Liu, ML Chee, C Niu, PP Pek, FJ Siddiqui, JP Ansah, DB Matchar, ... | | 2020 |