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

Applications of AI (923) Decision Support for Health Professionals (2190) Imaging Informatics (456) Theme Issue (2023): Generative & Multimodal AI in Digital Cardiovascular Medicine (9) Generative Language Models Including ChatGPT (1477) Cardiac Diagnostics (60)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74426, first published .
ECG monitor in hospital room showing patient vitals, including heart rate and brain activity.

Effectiveness of the GPT-4o Model in Interpreting Electrocardiogram Images for Cardiac Diagnostics: Diagnostic Accuracy Study

Effectiveness of the GPT-4o Model in Interpreting Electrocardiogram Images for Cardiac Diagnostics: Diagnostic Accuracy Study

Authors of this article:

Haya Engelstein1 Author Orcid Image ;   Roni Ramon-Gonen2 Author Orcid Image ;   Avi Sabbag3, 4 Author Orcid Image ;   Eyal Klang5, 6 Author Orcid Image ;   Karin Sudri7 Author Orcid Image ;   Michal Cohen-Shelly7 Author Orcid Image ;   Israel Barbash4, 8 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Zhu Y, Shu X, Liu X, Li Y, Yi B, Ma D. Applications and challenges of large language models in anesthesiology: narrative review and future perspectives. Anesthesiology and Perioperative Science 2025;3(4) 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
  3. Stelling H, Kraus A, Grieb G, Breidung D, Güler I. Artificial Intelligence for Biomedical Diagnostics: Diagnostic Accuracy and Reliability of Multimodal Large Language Models in Electrocardiogram Interpretation. Life 2026;16(4):681 View
  4. Soubh N, Rasenack E, Haarmann H, Wiedmann F, Zabel M, Schmidt C, Suliman R, Bergau L. Performance of Vision-Enabled Large Language Models in Image-Based Electrocardiogram Interpretation: Exploratory Evaluation. Journal of Medical Internet Research 2026;28:e86692 View
  5. Matsumoto K, Fujisaki Y, Higuchi S, Narita M, Sasaki W, Naganuma T, Tanaka N, Kawano D, Matsumoto K, Yoshino W, Ikeda Y, Kato R, Mori H. Large Language Model‐Based Localization of Premature Ventricular Contraction Origins: A Retrospective Diagnostic Accuracy Study. Journal of Cardiovascular Electrophysiology 2026 View

Conference Proceedings

  1. Touati M, Touati R, Medimegh M, Nana L, Mkaouer M. 2026 IEEE 5th International Conference on Computing and Machine Intelligence (ICMI). Pixheart: AI-Powered Automated ECG Analysis Using Hybrid CNN-LSTM and Machine Learning Models for Clinical Diagnostics View