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Improved Performance of ChatGPT-4 on the OKAP Exam: A Comparative Study with ChatGPT-3.5 [preprint]

Teebagy, Sean
Colwell, Lauren
Wood, Emma
Yaghy, Antonio
Faustina, Misha
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Abstract

This study aims to evaluate the performance of ChatGPT-4, an advanced Artificial Intelligence (AI) language model, on the Ophthalmology Knowledge Assessment Program (OKAP) examination compared to its predecessor, ChatGPT-3.5. Both models were tested on 180 OKAP practice questions covering various ophthalmology subject categories. Results showed that ChatGPT-4 significantly outperformed ChatGPT-3.5 (81% vs. 57%; p<0.001), indicating improvements in medical knowledge assessment. The superior performance of ChatGPT-4 suggests potential applicability in ophthalmologic education and clinical decision support systems. Future research should focus on refining AI models, ensuring a balanced representation of fundamental and specialized knowledge, and determining the optimal method of integrating AI into medical education and practice.

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Improved Performance of ChatGPT-4 on the OKAP Exam: A Comparative Study with ChatGPT-3.5. Sean Teebagy, Lauren Colwell, Emma Wood, Antonio Yaghy, Misha Faustina. medRxiv 2023.04.03.23287957; doi: https://doi.org/10.1101/2023.04.03.23287957

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10.1101/2023.04.03.23287957
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This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.

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This study did not receive any funding.
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The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.Attribution-NoDerivatives 4.0 International