Machine learning prediction of refractory ventricular fibrillation in out-of-hospital cardiac arrest using features available to EMS.

Autor: Rahadian RE; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore., Okada Y; Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.; Department of Preventive Services, Graduate School of Medicine, Kyoto University, Kyoto, Japan., Shahidah N; Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore.; Pre-hospital and Emergency Research Centre, Duke-NUS Medical School, Singapore., Hong D; Emergency Medical Services Department, Singapore Civil Defence Force, Singapore., Ng YY; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.; Department of Preventive and Population Medicine, Tan Tock Seng Hospital, Singapore, Singapore., Chia MYC; Emergency Department, Tan Tock Seng Hospital, Singapore, Singapore., Gan HN; Accident & Emergency, Changi General Hospital, Singapore, Singapore., Leong BSH; Emergency Medicine Department, National University Hospital, Singapore, Singapore., Mao DR; Department of Acute and Emergency Care, Khoo Teck Puat Hospital, Singapore, Singapore., Ng WM; Emergency Medicine Department, Ng Teng Fong General Hospital, Singapore, Singapore., Doctor NE; Department of Emergency Medicine, Sengkang General Hospital, Singapore, Singapore., Ong MEH; Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.; Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore.

Publikováno v: Resuscitation plus [Resusc Plus] 2024 Mar 18; Vol. 18, pp. 100606. Date of Electronic Publication: 2024 Mar 18 (Print Publication: 2024).