| Literature DB >> 33010796 |
Yue-Lin Wang1,2, Jing-Yun Yang3,4, Jing-Yuan Yang1,2, Xin-Yu Zhao1,2, You-Xin Chen1,2, Wei-Hong Yu1,2.
Abstract
Diabetic retinopathy (DR) is one of the leading causes of blindness worldwide, and the limited availability of qualified ophthalmologists restricts its early diagnosis. For the past few years, artificial intelligence technology has developed rapidly and has been applied in DR screening. The upcoming technology provides support on DR screening and improves the identification of DR lesions with a high sensitivity and specificity. This review aims to summarize the progress on automatic detection and classification models for the diagnosis of DR.Entities:
Keywords: artificial intelligence; deep learning; diabetic retinopathy; progress; review; screening
Mesh:
Year: 2020 PMID: 33010796 DOI: 10.1002/dmrr.3414
Source DB: PubMed Journal: Diabetes Metab Res Rev ISSN: 1520-7552 Impact factor: 4.876