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

Formative Evaluation of Digital Health Interventions (2858) Bots and AI Approaches to Detect and Counter Misinformation (11) Artificial Intelligence (AI) in Medical Education (128) Graduate and Postgraduate Education for Health Professionals (115) Chatbots and Conversational Agents (645) Generative Language Models Including ChatGPT (521)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63188, first published .
Comparing the Accuracy of Two Generated Large Language Models in Identifying Health-Related Rumors or Misconceptions and the Applicability in Health Science Popularization: Proof-of-Concept Study

Comparing the Accuracy of Two Generated Large Language Models in Identifying Health-Related Rumors or Misconceptions and the Applicability in Health Science Popularization: Proof-of-Concept Study

Comparing the Accuracy of Two Generated Large Language Models in Identifying Health-Related Rumors or Misconceptions and the Applicability in Health Science Popularization: Proof-of-Concept Study

Authors of this article:

Yuan Luo1 Author Orcid Image ;   Yiqun Miao1 Author Orcid Image ;   Yuhan Zhao1 Author Orcid Image ;   Jiawei Li1 Author Orcid Image ;   Yuling Chen2 Author Orcid Image ;   Yuexue Yue1 Author Orcid Image ;   Ying Wu1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

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