Variability in Large Language Models’ Responses to Medical Licensing and Certification Examinations. Comment on “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment”
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ChatGPT's output needs to be approached with a critical mindset, because misinformation may be more difficult to detect than in the output of other search engines that offer multiple sources and take login credentials into account.
“Thus, ChatGPT's output needs to be approached with a critical mindset, recognizing that misinformation may be more difficult to detect than in the output of other search engines that offer multiple sources in response to a query and take login credentials into account [8,55].”
From Comparison of the Performance of GPT-3.5 and GPT-4 With That of Medical Students on the Written German Medical Licensing Examination: Observational Study (2024) · cites this paper as [55]
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Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/45312 · Cited by 2,078 · see citing works
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A scoping review of artificial intelligence in medical education: BEME Guide No. 84
Gordon, M., Daniel, M., Ajiboye, A., Uraiby, H., Xu, N. Y., Bartlett, R., Hanson, J., Haas, M., Spadafore, M., Grafton-Clarke, C., et al. (2024) · Medical Teacher · doi:10.1080/0142159x.2024.2314198 · Cited by 543 · see citing works
Meyer, A., Riese, J., & Streichert, T. (2024) · JMIR Medical Education · doi:10.2196/50965 · Cited by 110 · see citing works
Sallam, M. (2023) · doi:10.1101/2023.02.19.23286155 · Cited by 3,123 · see citing works
“…in bias and inaccurate information limited to the period prior to the year 2021, and current inability to handle images, as well as the low performance in some topics (e.g., failure to pass a parasitology exam for Korean medical students) and the issue of possible plagiarism [51,60,62,63,67,68].”
Background
- Authors
- Epstein, R. H., & Dexter, F.
- Affiliations
- University of Miami (US)
- University of Iowa (US)
- Corresponding author
- Epstein, Richard H
- Venue
- JMIR Medical Education
- Publisher
- JMIR Publications Inc.
- Published
- 2023-07-13
- Volume
- 9
- Pages
- e48305
- ISSN
- 2369-3762 (ISSN-L)
- PMC
- PMC10375390
- OpenAlex
- W4381687070
- Cited by
- 26
- References
- 1
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 14 · 2023: 5
- FWCI
- 1.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Medical Education (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- large language models, ChatGPT, USMLE, medical licensing examinations, response variability, medical education, knowledge assessment, artificial intelligence in medical education
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