Open AccessAn Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging
Author(s) -
Alauddin Bhuiyan,
Arun Govindaiah,
Smith Rjh
Publication year - 2021
Publication title -
journal of ophthalmology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.818
H-Index - 40
eISSN - 2090-0058
pISSN - 2090-004X
DOI - 10.1155/2021/6694784
Subject(s) - glaucoma , medicine , artificial intelligence , fundus (uterus) , ophthalmology , optic disc , optic disk , optometry , computer science
Results The system achieved an accuracy of 89.67% (sensitivity, 83.33%; specificity, 93.89%; and AUC, 0.93). For external validation, the Retinal Fundus Image Database for Glaucoma Analysis dataset, which has 638 gradable quality images, was used. Here, the model achieved an accuracy of 83.54% (sensitivity, 80.11%; specificity, 84.96%; and AUC, 0.85).Conclusions Having demonstrated an accurate and fully automated glaucoma-suspect screening system that can be deployed on telemedicine platforms, we plan prospective trials to determine the feasibility of the system in primary-care settings.