Article
Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology.
American journal of human genetics - 1 Jul 2021
Alipanahi Babak, Hormozdiari Farhad, Behsaz Babak, Cosentino Justin, McCaw Zachary R, Schorsch Emanuel, Sculley D, Dorfman Elizabeth H, Foster Paul J, Peng Lily H, Phene Sonia, Hammel Naama, Carroll Andrew, Khawaja Anthony P, McLean Cory Y
Abstract excerpt
Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we develop a machine learning (ML) model to predict glaucomatous optic nerve head features from color fundus photographs. We used the model to predict vertical cup-to-disc ratio (VCDR), a diagnostic parameter and cardinal endophenotype for glaucoma, in 65,680...
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