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Paper Details

Usability and Clinician Acceptance of a Deep Learning-Based Clinical Decision Support Tool for Predicting Glaucomatous Visual Field Progression.
J Glaucoma
1
2023
Glaucomatous, glaucoma, patients
Artificial Intelligence, Decision Support Systems, Clinical, Deep Learning, Glaucoma, Humans, Intraocular Pressure, Visual Fields
Author NameAffiliation
Jimmy S ChenViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Jimmy S Chenuniversity of california san diego Health Department of Biomedical Informatics, University of California San Diego
Sally L BaxterViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Sally L Baxteruniversity of california san diego Health Department of Biomedical Informatics, University of California San Diego
Astrid van den BrandtEindhoven University of Technology
Alexander LieuViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Andrew S CampViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Jiun L DoViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Derek S WelsbieViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Sasan MoghimiViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Mark ChristopherViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Robert N WeinrebViterbi Family Department of Ophthalmology and Shiley Eye Institute.
Linda M ZangwillViterbi Family Department of Ophthalmology and Shiley Eye Institute.
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