Detecting glaucoma from multi-modal data using probabilistic deep learning

• Published in: Frontiers in medicine Vol. 9; p. 923096
• Main Authors: Huang, Xiaoqin, Sun, Jian, Gupta, Krati, Montesano, Giovanni, Crabb, David P., Garway-Heath, David F., Brusini, Paolo, Lanzetta, Paolo, Oddone, Francesco, Turpin, Andrew, McKendrick, Allison M., Johnson, Chris A., Yousefi, Siamak
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 29.09.2022
• Subjects: artificial intelligence; automated diagnosis; deep learning; fundus photograph; glaucoma; Medicine; visual field; deep learning; visual field; automated diagnosis; glaucoma; artificial intelligence; fundus photograph

To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields. Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control study. Fundus photog...