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大型语言模型在青光眼中的应用:一个范围的综述

Giovanni Rubegni¹, Alessandra Cartocci², Alessio Luschi²

¹Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, 53100 Siena, Italy.

Vision (Basel, Switzerland)

|February 20, 2026

概括

大型语言模型 (LLMs) 和视觉语言模型 (VLMs) 在格洛科马护理中显示出对患者教育和决策支持的希望. 然而,由于精度和集成的局限性,它们目前作为辅助工具的功能最好.

科学领域:

眼科医生眼科眼科
人工智能的人工智能
医疗信息学医疗信息学

背景情况:

大型语言模型 (LLM) 和视觉语言模型 (VLM) 在眼科中越来越多地用于患者教育,诊断和外科支持.
它们在处理医疗信息方面的能力使得它们在青光眼治疗中非常有价值.

研究的目的:

进行对绿眼中LLMs和VLMs的范围审查.
总结它们的应用,性能和局限性,以告知未来的研究和临床使用.

主要方法:

从2014年到2025年7月,在主要数据库 (PubMed,Scopus,Web of Science,arXiv,IEEE Xplore) 进行系统的文献搜索.
纳入研究的LLMs/VLMs在青光眼的诊断,教育,或手术支持.
根据PRISMA-ScR指南,由两个独立审查员进行选和审查.

主要成果:

27项研究符合316个已识别的记录中的包含标准.
应用被分为患者教育 (11项研究),诊断/风险预测 (10项研究) 和手术管理 (6项研究).

结论:

目前,LLM最适合作为青光眼护理中的辅助工具,而不是自主系统.
患者沟通和基于文本的决策支持的潜力很高,但准确性和多式联络整合需要改进.
未来的工作应该专注于特定领域的LLM,增强的多式联络融合,患者可读性和道德框架.

关键词:

聊天GPT 聊天在GPT 聊天人工智能是一种人工智能.临床决策支持临床决策支持玻璃眼 glaucoma 玻璃眼玻璃眼玻璃眼玻璃眼大型语言模型.患者教育患者教育视觉语言模型视觉语言模型

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