Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Alta.
Aurteen Inc., Calgary, Alta.
Can J Ophthalmol. 2018 Aug;53(4):309-313. doi: 10.1016/j.jcjo.2018.04.019. Epub 2018 May 30.
Deep learning is an emerging technology with numerous potential applications in Ophthalmology. Deep learning tools have been applied to different diagnostic modalities including digital photographs, optical coherence tomography, and visual fields. These tools have demonstrated utility in assessment of various disease processes including cataracts, glaucoma, age-related macular degeneration, and diabetic retinopathy. Deep learning techniques are evolving rapidly, and will become more integrated into ophthalmic care. This article reviews the current evidence for deep learning in ophthalmology, and discusses future applications, as well as potential drawbacks.
深度学习是一种新兴技术，在眼科领域有许多潜在的应用。深度学习工具已应用于不同的诊断方式，包括数字照片、光学相干断层扫描和视野。这些工具在评估各种疾病过程方面具有实用性，包括白内障、青光眼、年龄相关性黄斑变性和糖尿病性视网膜病变。深度学习技术发展迅速，将更多地融入眼科护理中。本文综述了深度学习在眼科领域的现有证据，并讨论了未来的应用以及潜在的缺点。
