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ORIGINAL RESEARCH article
Front. Med.
Sec. Healthcare Professions Education
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1534294
This article is part of the Research Topic Artificial Intelligence Applications in Chronic Ocular Diseases, Volume II View all 19 articles
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Background: Retinitis pigmentosa (RP) is a rare retinal dystrophy often underrepresented in ophthalmology education. Despite advancements in diagnostics and treatments like gene therapy, RP knowledge gaps persist. This study assesses the efficacy of AI-assisted teaching using ChatGPT compared to traditional methods in educating students about RP.Methods: A quasi-experimental study was conducted with 142 medical students randomly assigned to control (traditional review materials) and ChatGPT groups. Both groups attended a lecture on RP and completed pre-and post-tests. Statistical analyses compared learning outcomes, review times, and response accuracy.Results: Both groups significantly improved in post-test scores (p < 0.001), but the ChatGPT group required less review time (24.29±12.62 vs. 42.54±20.43 minutes, p < 0.0001). The ChatGPT group also performed better on complex questions regarding advanced RP treatments, demonstrating AI's potential to deliver accurate and current information efficiently.ChatGPT enhances learning efficiency and comprehension of rare diseases like RP. A hybrid educational model combining AI with traditional methods can address knowledge gaps, offering a promising approach for modern medical education.Introduction
Keywords: retinitis pigmentosa1, ChatGPT2, ophthalmology3, Education4, AI5
Received: 26 Nov 2024; Accepted: 03 Mar 2025.
Copyright: © 2025 Zeng, Sun, Qin and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Shulin Liu, First Affiliated Hospital of Chongqing Medical University, Chongqing, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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