Oganov Anthony C, Seddon Ian, Jabbehdari Sayena, Uner Ogul E, Fonoudi Hossein, Yazdanpanah Ghasem, Outani Oumaima, Arevalo J Fernando
Department of Ophthalmology, Renaissance School of Medicine, Stony Brook, NY, USA.
College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, USA.
Surv Ophthalmol. 2023 Sep-Oct;68(5):905-919. doi: 10.1016/j.survophthal.2023.04.001. Epub 2023 Apr 26.
Modern advances in diagnostic technologies offer the potential for unprecedented insight into ophthalmic conditions relating to the retina. We discuss the current landscape of artificial intelligence in retina with respect to screening, diagnosis, and monitoring of retinal pathologies such as diabetic retinopathy, diabetic macular edema, central serous chorioretinopathy, and age-related macular degeneration. We review the methods used in these models and evaluate their performance in both research and clinical contexts and discuss potential future directions for investigation, use of multiple imaging modalities in artificial intelligence algorithms, and challenges in the application of artificial intelligence in retinal pathologies.
诊断技术的现代进展为以前所未有的方式洞察与视网膜相关的眼科疾病提供了可能性。我们讨论了视网膜人工智能在糖尿病视网膜病变、糖尿病性黄斑水肿、中心性浆液性脉络膜视网膜病变和年龄相关性黄斑变性等视网膜疾病的筛查、诊断和监测方面的现状。我们回顾了这些模型中使用的方法，评估了它们在研究和临床环境中的性能，并讨论了未来潜在的研究方向、人工智能算法中多种成像模态的使用以及人工智能在视网膜疾病应用中的挑战。
