Accessibility settings

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

Applications of AI (344) AI Language Models in Health Care (248) Computer-Aided Diagnosis (278) Responsible Health AI (85) Cardiac Diagnostics (36) Machine Learning (2229) Clinical Information and Decision Making (2070) Artificial Intelligence (2347)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75910, first published .
Comparative Diagnostic Performance of a Multimodal Large Language Model Versus a Dedicated Electrocardiogram AI in Detecting Myocardial Infarction From Electrocardiogram Images: Comparative Study

Comparative Diagnostic Performance of a Multimodal Large Language Model Versus a Dedicated Electrocardiogram AI in Detecting Myocardial Infarction From Electrocardiogram Images: Comparative Study

Comparative Diagnostic Performance of a Multimodal Large Language Model Versus a Dedicated Electrocardiogram AI in Detecting Myocardial Infarction From Electrocardiogram Images: Comparative Study

Authors of this article:

Haemin Lee1, 2 Author Orcid Image ;   Sooyoung Yoo3 Author Orcid Image ;   Joonghee Kim1, 2 Author Orcid Image ;   Youngjin Cho2, 4 Author Orcid Image ;   Dongbum Suh1, 2 Author Orcid Image ;   Keehyuck Lee5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. 薛 齐. Research Progress and Application of Echocardiography, Cardiac Ultrasound, and Cardiac MRI in the Prognostic Value of AMI. Advances in Clinical Medicine 2026;16(02):1666 View
  2. Kokulu K, Akay M, Sert E. Accuracy of GPT-5 and GPT-4o in diagnosing STEMI from 12-Lead ECGs: A comparative study with cardiologists and emergency physicians. Heart & Lung 2026;78:102754 View