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Artificial Intelligence (4910) Clinical Information and Decision Making (3821) New Methods (1831) Advanced Data Analytics in eHealth (368) Machine Learning (3286) Cardiac Disease Management (203) Cardiac Risk and Cardiac Risk Calculators (183)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67576, first published .
Doctor analyzing ECG results on laptop with stethoscope and notebook

Deep Learning–Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study

Deep Learning–Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study

Authors of this article:

Shao-Chi Lu1 Author Orcid Image ;   Guang-Yuan Chen1 Author Orcid Image ;   An-Sheng Liu1 Author Orcid Image ;   Jen-Tang Sun2 Author Orcid Image ;   Jun-Wan Gao3 Author Orcid Image ;   Chien-Hua Huang3 Author Orcid Image ;   Chu-Lin Tsai3 Author Orcid Image ;   Li-Chen Fu1 Author Orcid Image
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  1. Lialiou P, Maglogiannis I. Students’ Burnout Symptoms Detection Using Smartwatch Wearable Devices: A Systematic Literature Review. AI Sensors 2025;1(1):2 View
  2. Feng N, Chen C, Du P, Gong C, Pei J, Huang D. MS-LTCAF: A Multi-Scale Lead-Temporal Co-Attention Framework for ECG Arrhythmia Detection. Bioengineering 2025;12(9):1007 View
  3. Han C, Soh S, Park J, Pak H, Yoon D. Artificial Intelligence–Based Electrocardiogram Model as a Predictor of Postoperative Atrial Fibrillation Following Cardiac Surgery: Retrospective Cohort Study. Journal of Medical Internet Research 2025;27:e77164 View
  4. Franceschi F, Ayar P, Hassan T, Gries A. Artificial intelligence to improve patient care in emergency medicine: a workflow-based analysis. Internal and Emergency Medicine 2026;21(1):29 View
  5. He S, Du M, Wang Z, Zang Y, Ning G, Pang S, Wan Y, Wang Y, Zuo M, Luan B, Duan N. Artificial intelligence in electrocardiogram signals for sudden cardiac death prediction: a systematic review and meta-analysis. Systematic Reviews 2025;15(1) View
  6. Silva D, Pretto G, Dominici S, Brandão A, Leal P. Artificial intelligence in cardiopulmonary resuscitation: a systematic review. Brazilian Journal of Anesthesiology (English Edition) 2026;76(5):844795 View
  7. Chen G, Lu S, Cheng W, Gao J, Sun J, Huang C, Tsai C, Fu L. Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study. BioData Mining 2026;19(1) View
  8. Olga A. Stelmakh , Anatolii M. Kravchenko . POSSIBILITIES OF APPLYING MACHINE LEARNING FOR ELECTROCARDIOGRAM ANALYSIS TO PREDICT MYOCARDIAL INFARCTION. The Ukrainian Scientific Medical Youth Journal 2026;164(3):128 View

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  1. Dinc R, Ardic N. Agentic Medicine. View

Conference Proceedings

  1. Azhagesan M, Shanmathi S, Anitha E, Ajithkumar S, Ramesh V, Gowrishankar O. 2026 9th International Conference on Computing Methodologies and Communication (ICCMC). Data-Driven Prediction System for Cardiac Arrest using Support Vector Machine (SVM) and Logistic Regression Algorithm (LR) View
  2. Simon A, Saji N, Krishnan M. 2026 4th International Conference on Sustainable Computing and Smart Systems (ICSCSS). Early Detection of Cardiac Arrest Risk using Clinical and ECG-Based AI Models View