Issa Mohamad, Sukkarieh Georges, Gallardo Mathias, Sarbout Ilias, Bonnin Sophie, Tadayoni Ramin, Milea Dan
Rothschild Foundation Hospital, Paris, France.
Rothschild Foundation Hospital, Paris, France; Sorbonne University, France.
Surv Ophthalmol. 2025 Mar-Apr;70(2):255-264. doi: 10.1016/j.survophthal.2024.11.007. Epub 2024 Nov 19.
Artificial intelligence(AI)-based methods have been extensively used for the detection and management of various common retinal conditions, but their targeted development for inherited retinal diseases (IRD) is still nascent. In the context of limited availability of retinal subspecialists, genetic testing and genetic counseling, there is a high need for accurate and accessible diagnostic methods. The currently available AI studies, aiming for detection, classification, and prediction of IRD, remain mainly retrospective and include relatively limited numbers of patients due to their scarcity. We summarize the latest findings and clinical implications of machine-learning algorithms in IRD, highlighting the achievements and challenges of AI to assist ophthalmologists in their clinical practice.
基于人工智能(AI)的方法已被广泛用于各种常见视网膜疾病的检测和管理,但其针对遗传性视网膜疾病(IRD)的针对性开发仍处于起步阶段。在视网膜专科医生、基因检测和遗传咨询有限的情况下,迫切需要准确且易于获得的诊断方法。目前可用的旨在检测、分类和预测IRD的AI研究主要仍是回顾性的,并且由于IRD患者稀缺,纳入的患者数量相对有限。我们总结了机器学习算法在IRD中的最新发现和临床意义,强调了AI在协助眼科医生临床实践方面的成就和挑战。