Published Erratum Epublish
PubMed: 41629405 DOI: 10.1038/s41746-025-02225-6
Author Correction: Leveraging AI and transfer learning to enhance out-of-hospital cardiac arrest outcome prediction in diverse setting.
NPJ Digit Med 9(1):103
Authors: Siqi Li, Yohei Okada, Wenjun Gu, Michael Hao Chen, Son Ngoc Do, Quyet Dinh Pham, Quoc Ta Hoang, Marcus Eng Hock Ong, Nan Liu
Affiliations
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
- Duke-NUS AI + Medical Sciences Initiative, Duke-NUS Medical School, Singapore, Singapore.
- Pre-hospital & Emergency Research Centre, Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
- Department of Preventive Services, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
- Center for Critical Care Medicine, Bach Mai Hospital, Hanoi, Vietnam.
- 115 Emergency Center, Ho Chi Minh, Vietnam.
- Emergency Department, Hue Central General Hospital, Hue, Vietnam.
- Health Services Research Centre, Singapore Health Services, Singapore, Singapore.
- Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore.
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
- Duke-NUS AI + Medical Sciences Initiative, Duke-NUS Medical School, Singapore, Singapore.
- Pre-hospital & Emergency Research Centre, Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
- NUS Artificial Intelligence Institute, National University of Singapore, Singapore, Singapore.
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
MeSH
Out-Of-Hospital Cardiac Arrest, Heart Arrest, Learning, Artificial Intelligence