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July 9, 2024Cureus9 citationsOpen Access

Advancing Medical Education: Performance of Generative Artificial Intelligence Models on Otolaryngology Board Preparation Questions With Image Analysis Insights

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ETEmma TerwilligerGBGeorge BcharahStructural Heart DiseaseHBHend BcharahArizona Department of Health Services

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Abstract

Objective To evaluate and compare the performance of Chat Generative Pre-Trained Transformer (ChatGPT), GPT-4, and Google Bard on United States otolaryngology board-style questions to scale their ability to act as an adjunctive study tool and resource for students and doctors. Methods A 1077 text question and 60 image-based questions from the otolaryngology board exam preparation tool BoardVitals were inputted into ChatGPT, GPT-4, and Google Bard. The questions were scaled true or false, depending on whether the artificial intelligence (AI) modality provided the correct response. Data analysis was performed in R Studio. Results GPT-4 scored the highest at 78.7% compared to ChatGPT and Bard at 55.3% and 61.7% (p0.05). On image-based questions, GPT-4 performed better than Bard (56.7% vs 46.4%, p=0.368) and had better overall image interpretation capabilities. Conclusion This study showed that the GPT-4 model performed better than both ChatGPT and Bard on the United States otolaryngology board practice questions. Although the GPT-4 results were promising, AI should still be used with caution when being implemented in medical education or patient care settings.

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Terwilliger et al. (2024) studied this question.

synapsesocial.com/papers/68e60e3db6db6435875a0ccchttps://doi.org/10.7759/cureus.64204
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