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

Artificial Intelligence (AI) in Medical Education (923) e-Learning and Digital Medical Education (1698) Testing and Assessment in Medical Education (255) New Methods and Approaches in Medical Education (698) Models and Frameworks in Medical Education (133) Machine Learning (3403) Development and Evaluation of Research Methods, Instruments and Tools (1487) Theme Issue: ChatGPT and Generative Language Models in Medical Education (144)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58898, first published .
Doctor reviews AI medical data on large screen and tablet.

Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study

Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study

Authors of this article:

Naritsaret Kaewboonlert1 Author Orcid Image ;   Jiraphon Poontananggul1 Author Orcid Image ;   Natthipong Pongsuwan1 Author Orcid Image ;   Gun Bhakdisongkhram1 Author Orcid Image
Article Authors Cited by (9) Tweetations Metrics

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  2. Shean R, Shah T, Pandiarajan A, Tang A, Bolo K, Nguyen V, Xu B. A comparative analysis of DeepSeek R1, DeepSeek-R1-Lite, OpenAi o1 Pro, and Grok 3 performance on ophthalmology board-style questions. Scientific Reports 2025;15(1) View
  3. Sudo H, Noborimoto Y, Takahashi J. Evaluation of Few-Shot AI-Generated Feedback on Case Reports in Physical Therapy Education: Mixed Methods Study. JMIR Medical Education 2025;11:e85614 View
  4. Reis F, Agha-Mir-Salim L, Hickstein R, Reis M, Piper S, Balzer F, Boie S. Disclaimers and Referral Patterns for Medical Advice Across Urgency Levels: Large Language Model Evaluation Study. Journal of Medical Internet Research 2026;28:e84668 View
  5. Chen K, Rogers K, Haberkorn W, Lew M, Kanegan J, Nam H, Chantra J, Asch S, Lee G. AI-driven analysis of patient safety reports using large language models: an exploratory multiple methods study. BMJ Quality & Safety 2026:bmjqs-2025-019495 View
  6. El Natour D, Abou Alfa M, Chaaban A, Assi R, Dally T, Bou Dargham B. Performance of 5 AI Models on United States Medical Licensing Examination Step 1 Questions: Comparative Observational Study. JMIR AI 2026;5:e76928 View
  7. Stephenson E, Robinson S, Bascombe K, Okorie M. Secure AI-assisted angoff standard-setting for single best answer questions: A non-inferiority validation study. Medical Teacher 2026:1 View
  8. Gündoğdu Öğütlü Ö, Solomon B, Çelik Y. Benchmarking five large language models in medical genetics: a bilingual comparative evaluation using published and novel expert-authored questions. Frontiers in Medicine 2026;13 View
  9. Leonforte F, Cavallaro A, Nicosia V, Scapellato A, Gambera A, Genovese C, Mistretta A, Zanghì A, Basile G, Veroux M, Di Mattia P, Calabrò A, Tiralongo K, Gatthas Y. Artificial Intelligence in Medical and Surgical Information: A Systematic Review of Accuracy, Readability, Reliability, and Emotional Resonance. AI 2026;7(10):396 View