Analysis reveals ChatGPT's strengths and weaknesses in tackling ophthalmology exam questions, indicating its potential in medical education.
Background: ChatGPT is a large-scale language model trained on various datasets to learn, analyze, and generate human-like answers to user's questions. To assess its applicability to medical education, more information is required to understand whether its analyses can provide accurate and coherent responses to questions. The aim of this study was to characterize ChatGPT responses to ophthalmology questions according to subtopic to determine where the system might be used reliably in resident education and where its performance remains weak.
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Cartagena et al. (2025) studied this question.
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