[HTML][HTML] Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs
Purpose To develop and validate a deep learning (DL) algorithm that predicts referable
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color
fundus images, to determine the relative importance of these features in referral decisions by
glaucoma specialists (GSs) and the algorithm, and to compare the performance of the
algorithm with eye care providers. Design Development and validation of an algorithm.
Participants Fundus images from screening programs, studies, and a glaucoma clinic …
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color
fundus images, to determine the relative importance of these features in referral decisions by
glaucoma specialists (GSs) and the algorithm, and to compare the performance of the
algorithm with eye care providers. Design Development and validation of an algorithm.
Participants Fundus images from screening programs, studies, and a glaucoma clinic …
[PDF][PDF] Deep Learning and Glaucoma Specialists The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
Purpose: To develop and validate a deep learning (DL) algorithm that predicts referable
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color
fundus images, to determine the relative importance of these features in referral decisions by
glaucoma specialists (GSs) and the algorithm, and to compare the performance of the
algorithm with eye care providers. Design: Development and validation of an algorithm.
Participants: Fundus images from screening programs, studies, and a glaucoma clinic …
glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color
fundus images, to determine the relative importance of these features in referral decisions by
glaucoma specialists (GSs) and the algorithm, and to compare the performance of the
algorithm with eye care providers. Design: Development and validation of an algorithm.
Participants: Fundus images from screening programs, studies, and a glaucoma clinic …
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