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

Research Letter (48) Clinical Informatics (1174) Chatbots and Conversational Agents (642) Generative Language Models Including ChatGPT (516) Artificial Intelligence (1767) Digital Health, Telehealth and e-Innovation in Clinical Settings (480) Decision Support for Health Professionals (1355) Methods and Instruments in Medical Informatics (167) Ontologies, Classifications, and Coding (275)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53724, first published .
Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases

Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases

Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases

Authors of this article:

Wan Hang Keith Chiu1 Author Orcid Image ;   Wei Sum Koel Ko1 Author Orcid Image ;   William Chi Shing Cho2 Author Orcid Image ;   Sin Yu Joanne Hui3 Author Orcid Image ;   Wing Chi Lawrence Chan4 Author Orcid Image ;   Michael D Kuo5 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

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  1. Shmilovitch A, Katson M, Cohen-Shelly M, Peretz S, Aran D, Shelly S. GPT-4 as a Clinical Decision Support Tool in Ischemic Stroke Management: Evaluation Study. JMIR AI 2025;4:e60391 View
  2. Takita H, Kabata D, Walston S, Tatekawa H, Saito K, Tsujimoto Y, Miki Y, Ueda D. A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians. npj Digital Medicine 2025;8(1) View
  3. Lafourcade C, Kérourédan O, Ballester B, Richert R. Accuracy, consistency, and contextual understanding of large language models in restorative dentistry and endodontics. Journal of Dentistry 2025;157:105764 View