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

The GPT-4 and Microsoft Bing models demonstrated equal and superior accuracy compared to GPT-3.5 and Google Bard in the domain of basic medical science. The accuracy of these models was significantly influenced by the item's difficulty index, indicating that the LLMs are more accurate when answering easier questions. This suggests that the more accurate models, such as GPT-4 and Bing, can be valuable tools for understanding and learning basic medical science concepts.

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Publication Details

Journal
JMIR Medical Education
Published
2024-12-04
DOI
https://doi.org/10.2196/58898
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.72
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article

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

Natthipong Pongsuwan, Gun Bhakdisongkhram, Naritsaret Kaewboonlert, Jiraphon Poontananggul
6 citations
JMIR Medical Education
Artificial Intelligence in Healthcare and Education
0.72
article

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

Natthipong Pongsuwan, Gun Bhakdisongkhram, Naritsaret Kaewboonlert, Jiraphon Poontananggul
article en
6 citations

Abstract

The GPT-4 and Microsoft Bing models demonstrated equal and superior accuracy compared to GPT-3.5 and Google Bard in the domain of basic medical science. The accuracy of these models was significantly influenced by the item's difficulty index, indicating that the LLMs are more accurate when answering easier questions. This suggests that the more accurate models, such as GPT-4 and Bing, can be valuable tools for understanding and learning basic medical science concepts.

JMIR Medical EducationVol. 11
Suranaree University of Technology (TH)
Quality Education
Openalex Percentile: Top 26%
Artificial Intelligence in Healthcare and Education
0.72
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Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study — Natthipong Pongsuwan, Gun Bhakdisongkhram, et al. · JMIR Medical Education (2024) | TGRS Research Map | TGRS