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

Generative Language Models Including ChatGPT (797) Chronic Conditions (475) e-Learning and Digital Medical Education (955) Artificial Intelligence (AI) in Medical Education (227) Foundation Models and Their Applications in AI (55) Ethical, Legal, and Social Issues in AI (122)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62857, first published .
Ability of ChatGPT to Replace Doctors in Patient Education: Cross-Sectional Comparative Analysis of Inflammatory Bowel Disease

Ability of ChatGPT to Replace Doctors in Patient Education: Cross-Sectional Comparative Analysis of Inflammatory Bowel Disease

Ability of ChatGPT to Replace Doctors in Patient Education: Cross-Sectional Comparative Analysis of Inflammatory Bowel Disease

Authors of this article:

Zelin Yan1, 2, 3 Author Orcid Image ;   Jingwen Liu2 Author Orcid Image ;   Yihong Fan1 Author Orcid Image ;   Shiyuan Lu2 Author Orcid Image ;   Dingting Xu2 Author Orcid Image ;   Yun Yang4 Author Orcid Image ;   Honggang Wang5 Author Orcid Image ;   Jie Mao6 Author Orcid Image ;   Hou-Chiang Tseng7 Author Orcid Image ;   Tao-Hsing Chang8 Author Orcid Image ;   Yan Chen2, 3 Author Orcid Image
Article Authors Cited by (10) Tweetations (1) Metrics

Journals

  1. Ozturk O, Ergul M, Cagir Y, Atay A, Acun K, Coskun O, Tenlik I, Durak M, Yuksel I. Assessing ChatGPT-v4 for Guideline-Concordant Inflammatory Bowel Disease: Accuracy, Completeness, and Temporal Drift. Journal of Clinical Medicine 2025;14(13):4599 View
  2. 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
  3. Belkhouribchia J, Pen J. Large language models in clinical nutrition: an overview of its applications, capabilities, limitations, and potential future prospects. Frontiers in Nutrition 2025;12 View
  4. Bahir D, Hartstein M, Burkat C, Ezra D, Wulc A, Zloto O, Holds J, Hamed Azzam S. Revolutionizing Patient Education: Artificial Intelligence Versus Experts in Ocular Dyskinesia Responses. Ophthalmic Plastic & Reconstructive Surgery 2026;42(2):172 View
  5. Liu S, Su L, He Q, Qiu M, Liang R. Comparative evaluation of ChatGPT and Gemini in brain-computer interfaces patient education: A multi-dimensional analysis of reliability, accuracy, comprehensibility, and readability. International Journal of Medical Informatics 2026;206:106164 View
  6. Jin Z, Zun C, Liang S, Sida L, Dong L, Fei X, Qingfang Y, Yuting W, Jinping Z, Yuling W, Bopeng C, Xianglong D. The reliability and quality of short videos as health information of guidance for bowel sounds: a cross-sectional study. Frontiers in Public Health 2025;13 View
  7. Shen S, Zhou K, Wu M, Liu D, Shen X, Li P, Xu Y, Zheng S, Gou X. Feeding intelligence: comparative evaluation of ChatGPT and clinical guidelines for nutritional management in head and neck cancer. Journal of Translational Medicine 2025;23(1) View
  8. Burleson L, Boardley E, LaShell A, Shanks A. The OB-GYN Take on GPT: Objective Assessment of Artificial Intelligence Models in Patient Education. Cureus 2026 View
  9. Richter S, Buszello C, Prem M, Willkommen S, Hasani E, Uckermann O, Sandi-Gahun S, Juratli T, Eyüpoglu I, Polanski W. Impact of Large Language Model–Based AI Tools on Physician–Patient Communication: A Systematic Review and Meta-Analysis (Preprint). Journal of Medical Internet Research 2025 View
  10. Dhanoa A, Lafreniere A, Harper C, Kim G, Saenz L, Persitz J, Zuo K. Evaluating Generative Artificial Intelligence Models’ Responses to Questions About Scaphoid Fracture and Scaphoid Nonunion. Journal of Hand Surgery Global Online 2026;8(3):100978 View