Development and validation of an interpretable prehospital return of spontaneous circulation (P-ROSC) score for patients with out-of-hospital cardiac arrest using machine learning: A retrospective study

eClinicalMedicine - Tập 48 - Trang 101422 - 2022
Nan Liu1,2,3,4,5, Mingxuan Liu1, Xinru Chen1, Yilin Ning1, Jin Wee Lee1, Fahad Javaid Siddiqui1, Seyed Ehsan Saffari1,6, Andrew Fu Wah Ho1,7, Sang Do Shin8, Matthew Huei-Ming Ma9, Hideharu Tanaka10, Marcus Eng Hock Ong1,2,7
1Duke-NUS Medical School, National University of Singapore, 8 College Road, Singapore 169857, Singapore
2Health Services Research Centre, Singapore Health Services, Singapore, Singapore
3SingHealth AI Health Program, Singapore Health Services, Singapore, Singapore
4SingHealth Duke-NUS Global Health Institute, Singapore, Singapore
5Institute of Data Science, National University of Singapore, Singapore, Singapore
6National Neuroscience Institute, Singapore, Singapore
7Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore
8Department of Emergency Medicine, School of Medicine, Seoul National University, Seoul, Republic of Korea
9Department of Emergency Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan
10Graduate School of Emergency Medical System, Kokushikan University, Tokyo, Japan

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