Open AccessComparison of Autonomous AS-OCT Deep Learning Algorithm and Clinical Dry Eye Tests in Diagnosis of Dry Eye Disease
Author(s) -
Collin Chase,
Amr Elsawy,
Taher Eleiwa,
Eyüp Özcan,
Mohamed Tolba,
Mohamed Abou Shousha
Publication year - 2021
Publication title -
clinical ophthalmology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.025
H-Index - 56
eISSN - 1177-5483
pISSN - 1177-5467
DOI - 10.2147/opth.s321764
Subject(s) - medicine , ophthalmology , gold standard (test) , cornea , optical coherence tomography , medical diagnosis , slit lamp , likelihood ratios in diagnostic testing , artificial intelligence , diagnostic accuracy , pathology , radiology , computer science
To evaluate a deep learning-based method to autonomously detect dry eye disease (DED) in anterior segment optical coherence tomography (AS-OCT) images compared to common clinical dry eye tests.