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

Generative Language Models Including ChatGPT (521) Quality/Credibility of eHealth Information and Trust Issues (607) Chatbots and Conversational Agents (645) Artificial Intelligence (1776) AI Language Models in Health Care (112) Information Quality in Digital Media (378)

Published on in Vol 26 (2024)

This is a member publication of University of California, Irvine, Emergency Medicine, Orange, California

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60291, first published .
Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study

Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study

Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study

Authors of this article:

Jonathan Yi-Shin Yau1 Author Orcid Image ;   Soheil Saadat2 Author Orcid Image ;   Edmund Hsu2 Author Orcid Image ;   Linda Suk-Ling Murphy3 Author Orcid Image ;   Jennifer S Roh4 Author Orcid Image ;   Jeffrey Suchard2 Author Orcid Image ;   Antonio Tapia2 Author Orcid Image ;   Warren Wiechmann2 Author Orcid Image ;   Mark I Langdorf2 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

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  6. Hegedűs M, Dadkhah M, Dávid L. Benchmarking AI chatbots: assessing their accuracy in identifying hijacked medical journals. Diagnosis 2025 View
  7. Shen M, Li Z, Wu J. A commentary on “Bots in white coats: are large language models the future of patient education? A multicenter cross-sectional analysis”. International Journal of Surgery 2025;111(6):4149 View