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

Formative Evaluation of Digital Health Interventions (5471) Information Seeking, Information Needs (672) Information Demand (68) Obesity (142) Generative Language Models Including ChatGPT (1679)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78289, first published .
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Accuracy of Large Language Model Responses Versus Internet Searches for Common Questions About Glucagon-Like Peptide-1 Receptor Agonist Therapy: Exploratory Simulation Study

Accuracy of Large Language Model Responses Versus Internet Searches for Common Questions About Glucagon-Like Peptide-1 Receptor Agonist Therapy: Exploratory Simulation Study

Authors of this article:

Sarah Ying Tse Tan1 Author Orcid Image ;   Gerald Gui Ren Sng1 Author Orcid Image ;   Phong Ching Lee1 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Trillo-Domínguez M, Martin-Neira J, Olvera-Lobo M. Dr. Google vs. Dr. ChatGPT in Online Health Self-Consultation: A Scoping Review of Accuracy, Bias, and Actionability (2023–2025). Informatics 2026;13(3):41 View
  2. Engin İ, Çelik Tufan M, Arda Özkan E. Comparative Evaluation of Claude, Gemini, and ChatGPT in Responding to Patient Inquiries About Hyperprolactinemia and Prolactinoma: A Multi-Rater Cross-Sectional Study Using English-Language Queries. Farabi Tıp Dergisi 2026;5(1) View
  3. Wójcik S, Domienik-Karłowicz J, Rulkiewicz A. Synthetic gatekeeping in health chatbots: configured answer systems as the unit of AI evaluation and governance for medical information. Frontiers in Digital Health 2026;8 View
  4. Aladag E. Guideline Adherence, Clinical Safety, and Source Accuracy of Commercial Large Language Models in Perioperative GLP-1 and GLP-1/GIP Receptor Agonist Management: A Scenario-Based Comparative Study. Acta Medica Alanya 2026;10(3):209 View