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眼科前段疾病中的人工智能

Artificial intelligence in the anterior segment of eye diseases.

作者信息

Liu Yao-Hong, Li Lin-Yu, Liu Si-Jia, Gao Li-Xiong, Tang Yong, Li Zhao-Hui, Ye Zi

机构信息

School of Medicine, Nankai University, Tianjin 300071, China.

Department of Ophthalmology, Chinese PLA General Hospital, Beijing 100039, China.

出版信息

Int J Ophthalmol. 2024 Sep 18;17(9):1743-1751. doi: 10.18240/ijo.2024.09.23. eCollection 2024.

Abstract

Ophthalmology is a subject that highly depends on imaging examination. Artificial intelligence (AI) technology has great potential in medical imaging analysis, including image diagnosis, classification, grading, guiding treatment and evaluating prognosis. The combination of the two can realize mass screening of grass-roots eye health, making it possible to seek medical treatment in the mode of "first treatment at the grass-roots level, two-way referral, emergency and slow treatment, and linkage between the upper and lower levels". On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology, quite a lot of studies have confirmed that machine learning can assist in diagnosis, grading, providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases, ametropia, lens diseases, glaucoma, iris diseases, . This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases, the current limitations, and prospects for the future.

摘要

眼科是一门高度依赖影像学检查的学科。人工智能(AI)技术在医学影像分析中具有巨大潜力,包括图像诊断、分类、分级、指导治疗和评估预后。两者结合可实现基层眼健康的大规模筛查,使“基层首诊、双向转诊、急慢分治、上下联动”的就医模式成为可能。在总结世界各地学者及其团队在眼科领域开展的人工智能技术的基础上,相当多的研究证实,机器学习可辅助诊断、分级、提供最佳治疗方案以及评估角膜和结膜疾病、屈光不正、晶状体疾病、青光眼、虹膜疾病等的预后。本文系统展示了人工智能技术在常见眼前段眼部疾病中的应用与进展、当前存在的局限性以及未来展望。

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