Wu Jo-Hsuan, Lin Shan, Moghimi Sasan
Shiley Eye Institute and Viterbi Family Department of Ophthalmology, University of California San Diego, La Jolla, California.
Edward S. Harkness Eye Institute, Department of Ophthalmology, Columbia University Irving Medical Center, New York.
Taiwan J Ophthalmol. 2024 Sep 13;14(3):340-351. doi: 10.4103/tjo.TJO-D-24-00044. eCollection 2024 Jul-Sep.
The application of artificial intelligence (AI) in ophthalmology has been increasingly explored in the past decade. Numerous studies have shown promising results supporting the utility of AI to improve the management of ophthalmic diseases, and glaucoma is of no exception. Glaucoma is an irreversible vision condition with insidious onset, complex pathophysiology, and chronic treatment. Since there remain various challenges in the clinical management of glaucoma, the potential role of AI in facilitating glaucoma care has garnered significant attention. In this study, we reviewed the relevant literature published in recent years that investigated the application of AI in glaucoma management. The main aspects of AI applications that will be discussed include glaucoma risk prediction, glaucoma detection and diagnosis, visual field estimation and pattern analysis, glaucoma progression detection, and other applications.
在过去十年中，人工智能（AI）在眼科领域的应用得到了越来越多的探索。大量研究已显示出令人鼓舞的结果，支持人工智能在改善眼科疾病管理方面的效用，青光眼也不例外。青光眼是一种具有隐匿性发病、复杂病理生理学和长期治疗特点的不可逆视力疾病。由于青光眼的临床管理仍存在各种挑战，人工智能在促进青光眼护理方面的潜在作用已引起了广泛关注。在本研究中，我们回顾了近年来发表的有关人工智能在青光眼管理中应用的相关文献。将讨论的人工智能应用的主要方面包括青光眼风险预测、青光眼检测与诊断、视野估计与模式分析、青光眼进展检测以及其他应用。
