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

Machine Learning (2076) Myocardial Infarction (Heart Attack) (56) Advanced Data Analytics in eHealth (209) Decision Support for Health Professionals (1539) Tools, Programs and Algorithms (376) Artificial Intelligence (2129) Clinical Informatics (1325) Clinical Information and Decision Making (1915)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49142, first published .
Prediction of In-Hospital Cardiac Arrest in the Intensive Care Unit: Machine Learning–Based Multimodal Approach

Prediction of In-Hospital Cardiac Arrest in the Intensive Care Unit: Machine Learning–Based Multimodal Approach

Prediction of In-Hospital Cardiac Arrest in the Intensive Care Unit: Machine Learning–Based Multimodal Approach

Authors of this article:

Hsin-Ying Lee1 Author Orcid Image ;   Po-Chih Kuo2 Author Orcid Image ;   Frank Qian3, 4 Author Orcid Image ;   Chien-Hung Li2 Author Orcid Image ;   Jiun-Ruey Hu5 Author Orcid Image ;   Wan-Ting Hsu6 Author Orcid Image ;   Hong-Jie Jhou7 Author Orcid Image ;   Po-Huang Chen8 Author Orcid Image ;   Cho-Hao Lee9 Author Orcid Image ;   Chin-Hua Su10 Author Orcid Image ;   Po-Chun Liao10 Author Orcid Image ;   I-Ju Wu10 Author Orcid Image ;   Chien-Chang Lee10, 11 Author Orcid Image
Article Authors Cited by (11) Tweetations Metrics

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  1. Ni P, Zhang S, Hu W, Diao M. Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest. Resuscitation Plus 2024;20:100829 View
  2. Sang W, Ma J, Zhang X, Wu S, Pan C, Zheng J, Zheng W, Yuan Q, Zhang J, Ma J, Xu F. Early prediction cardiac arrest in intensive care units: the value of laboratory indicator trends. World Journal of Emergency Medicine 2025;16(1):67 View
  3. Kim S. Enhancing Clinical Cardiac Care: Predicting In-Hospital Cardiac Arrest With Machine Learning. Annals of Laboratory Medicine 2025;45(2):117 View
  4. Wang J, Hsu S, Sun J, Ko C, Huang C, Tsai C, Fu L. Internal and External Validation of a Deep Learning-Based Early Warning System of Cardiac Arrest with Variable-Length and Irregularly Measured Time Series Data. Journal of Healthcare Informatics Research 2025 View
  5. Roedl K, Genbrugge C. Managing cardiac arrest in the intensive care unit. Current Opinion in Critical Care 2025;31(6):729 View
  6. Naresh V, Vineela M. Enhanced Prediction of Cardiac Risk in Neonates Using Calibrated Ensemble Learning Approaches. Pediatric Cardiology 2025 View
  7. Zhang Y, Tang H, Ying L, Zhang L, Zhang L. Cardiac Arrest, Patient Characteristics and Prognosis: a Machine Learning Approach. Kardiologiia 2025;65(10):91 View
  8. Zhao P, Tong Y, Du Z, Ma S, Fan B. Key physiological indicators and technological trends in physiology-directed cardiopulmonary resuscitation: A narrative review. Resuscitation Plus 2025:101180 View

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