This paper is in the following e-collection/theme issue:

Digital Health Reviews (1741) Clinical Information and Decision Making (1935) Decision Support for Health Professionals (1555) Machine Learning (2095) Artificial Intelligence (2161) Cardiac Disease Management (160) Cardiac Risk and Cardiac Risk Calculators (107)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67871, first published .
Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis

Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis

Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis

Authors of this article:

Shengfeng Wei1 Author Orcid Image ;   Xiangjian Guo1 Author Orcid Image ;   Shilin He1 Author Orcid Image ;   Chunhua Zhang1 Author Orcid Image ;   Zhizhuan Chen1 Author Orcid Image ;   Jianmei Chen1 Author Orcid Image ;   Yanmei Huang1 Author Orcid Image ;   Fan Zhang1 Author Orcid Image ;   Qiangqiang Liu1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Puticiu M, Pop F, Butoi M, Banicioiu-Covei M, Rotaru L, Blaga T, Cimpoesu D. Artificial Intelligence in Cardiopulmonary Resuscitation. Medicina 2025;61(12):2099 View
  2. Bamodu O, Goh Y, Hong C, Chen P, Chiu W, Chan L, Chung C. Explainable machine learning for neurological outcome prediction in out-of-hospital cardiac arrest survivors undergoing targeted temperature management: a multi-cohort validation study. Journal of NeuroEngineering and Rehabilitation 2025 View