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

Scoping Review Protocols (530) Clinical Information and Decision Making (3570) Decision Support for Health Professionals (2137) Machine Learning (3072) Cardiac Risk and Cardiac Risk Calculators (166) Artificial Intelligence (4575)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69716, first published .
Runner's chest with glowing red EKG heart rate graphic

Predicting In-Hospital Cardiac Arrest Using Machine Learning Models: Protocol for a Scoping Review

Predicting In-Hospital Cardiac Arrest Using Machine Learning Models: Protocol for a Scoping Review

Authors of this article:

Mina Attin1 Author Orcid Image ;   Bryar Shareef1 Author Orcid Image ;   Nelson Appiah-Agyei1 Author Orcid Image ;   Farzana Mahamud Rini1 Author Orcid Image ;   Xan Goodman1 Author Orcid Image ;   Lauren Bredesky1 Author Orcid Image ;   Jonathan A Chavez1 Author Orcid Image ;   Rawa Mohammed1 Author Orcid Image ;   Kavita Batra1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Attin M, Shareef B, Appiah-Agyei N, Rini F, Goodman X, Bredesky L, Chavez J, Mohammed R, Batra K. Predicting In-Hospital Cardiac Arrest Using Machine Learning Models: A Scoping Review. Artificial Intelligence in Emergency Medicine 2026;1:100007 View
  2. Jiang T, Liu J, Hu D, Diao M, Cao J. In‐Hospital Cardiac Arrest Detection Performance Analysis and Comparison on Effective Feature Selection. Clinical Cardiology 2026;49(7) View

Conference Proceedings

  1. Chawla P, Girija R, Tyagi S, Bhardwaj D, Dagar R, Saini A. 2025 3rd International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT). Prediction of Cardiac Arrest Using Machine Learning and Deep Learning Algorithms View