Artificial intelligence in clinical education in ophthalmology: a systematic review

作者：Lu Yuan, Daohuan Kang, Xinran Dong, Lei Liu, Andrzej Grzybowski, Kai Jin · 发表于：Visual Neuroscience · 年份：2025 · DOI：10.48130/vns-0025-0025 · 被引用次数：8 · 研究领域：Ophthalmology and Visual Health Research、Retinal Imaging and Analysis、Retinal and Optic Conditions

The application of artificial intelligence (AI) in ophthalmological clinical education has attracted widespread attention. This systematic review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and searched three electronic databases (PubMed, Google Scholar, and Web of Science) for literature published between 1 January 2019 and 31 May 2025. In total, 38 studies were included to evaluate the role of AI in ophthalmological education. The results indicate that AI enhances the screening and diagnostic capabilities for ophthalmic diseases through big data and deep learning algorithms, while also diversifying educational approaches. Technologies such as virtual reality (VR), augmented reality (AR), and intelligent tutoring systems create immersive learning environments that support surgical simulation, real-time feedback, and personalized learning pathways, significantly improving students' engagement and skill acquisition. Furthermore, AI-assisted image analysis and automated annotation tools optimize educational resources, shorten the duration of learning, and improve diagnostic accuracy. Nevertheless, challenges remain in the promotion of AI, including issues related to data quality, privacy protection, and ethical considerations.