Artificial intelligence-assisted diagnosis of ocular surface diseases - Zhang, Zuhui; Wang, Ying; Zhang, Hongzhen; Samusak, Arzigul; Rao, Huimin; Xiao, Chun; Abula, Muhetaer; Cao, Qixin; Dai, Qi (Frontiers in Cell and Developmental Biology, 2023)
With the rapid development of computer technology, the application of artificial intelligence (AI) in ophthalmology research has gained prominence in modern medicine. AI-related research in ophthalmology previously focused on the screening and diagnosis of fundus diseases, particu-larly diabetic retinopathy, age-related macular degeneration, and glaucoma. Since fundus images are relatively fixed, their standards are easy to unify. AI research related to ocular surface dis-eases has also increased. The main issue with research on ocular surface diseases is that the im-ages involved are complex, with many modalities. Therefore, this review aims to summarize current AI research and technologies used to diagnose ocular surface diseases such as pterygium, keratoconus, infectious keratitis, and dry eye to identify mature AI models that are suitable for research of ocular surface diseases and potential algorithms that may be used in the future.