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

Research Letter (38) Digital Health, Telehealth and e-Innovation in Clinical Settings (420) Artificial Intelligence (1409) Chatbots and Conversational Agents (542) Generative Language Models Including ChatGPT (320) Cardiology (163) Decision Support for Health Professionals (1203)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54607, first published .
Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations

Authors of this article:

Lingxuan Zhu1 Author Orcid Image ;   Weiming Mou2 Author Orcid Image ;   Keren Wu1 Author Orcid Image ;   Yancheng Lai1 Author Orcid Image ;   Anqi Lin1 Author Orcid Image ;   Tao Yang3 Author Orcid Image ;   Jian Zhang1 Author Orcid Image ;   Peng Luo1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Günay S, Öztürk A, Yiğit Y. The accuracy of Gemini, GPT-4, and GPT-4o in ECG analysis: A comparison with cardiologists and emergency medicine specialists. The American Journal of Emergency Medicine 2024;84:68 View
  2. Meddeb A, Ebert P, Bressem K, Desser D, Dell'Orco A, Bohner G, Kleine J, Siebert E, Grauhan N, Brockmann M, Othman A, Scheel M, Nawabi J. Evaluating local open-source large language models for data extraction from unstructured reports on mechanical thrombectomy in patients with ischemic stroke. Journal of NeuroInterventional Surgery 2024:jnis-2024-022078 View
  3. Avidan Y, Tabachnikov V, Court O, Khoury R, Aker A. In the face of confounders: Atrial fibrillation detection – Practitioners vs. ChatGPT. Journal of Electrocardiology 2024:153851 View