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

AI Language Models in Health Care (200) Innovations in Mental Health Systems (484) Natural Language Processing (912) Artificial Intelligence (2117) Depression and Mood Disorders; Suicide Prevention (1683) Machine Learning (2070) Clinical Information and Decision Making (1910) Decision Support for Health Professionals (1535) Generative Language Models Including ChatGPT (704)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64318, first published .
Performance Assessment of Large Language Models in Medical Consultation: Comparative Study

Performance Assessment of Large Language Models in Medical Consultation: Comparative Study

Performance Assessment of Large Language Models in Medical Consultation: Comparative Study

Authors of this article:

Sujeong Seo1, 2 Author Orcid Image ;   Kyuli Kim1 Author Orcid Image ;   Heyoung Yang1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Yang H, Li M, Zhou H, Xiao Y, Fang Q, Zhou S, Zhang R. Large Language Model Synergy for Ensemble Learning in Medical Question Answering: Design and Evaluation Study. Journal of Medical Internet Research 2025;27:e70080 View
  2. Guo S, Song Y, Chen G, Han H, Wu H, Ma J. Promoting trust and intention to adopt health information generated by ChatGPT among healthcare customers: An empirical study. DIGITAL HEALTH 2025;11 View
  3. XU X, LI H, GUAN Z, ZENG D, ZHENG Q, QIN Y, WEN Y, LI H, LIM C, Yin WONG T, WU E, JIA W, SHENG B. Urgent needs, opportunities and challenges of virtual reality in healthcare and medicine in the era of large language models. Virtual Reality & Intelligent Hardware 2025;7(5):453 View