Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs.

ABSTRACT:

Objective

To evaluate the performance of a deep learning system (DLS) in classifying the severity of papilledema associated with increased intracranial pressure on standard retinal fundus photographs.

Methods

A DLS was trained to automatically classify papilledema severity in 965 patients (2,103 mydriatic fundus photographs), representing a multiethnic cohort of patients with confirmed elevated intracranial pressure. Training was performed on 1,052 photographs with mild/moderate papilledema (MP) and 1,051 photographs with severe papilledema (SP) classified by a panel of experts. The performance of the DLS and that of 3 independent neuro-ophthalmologists were tested in 111 patients (214 photographs, 92 with MP and 122 with SP) by calculating the area under the receiver operat

SUBMITTER: Vasseneix C 

PROVIDER: S-EPMC8362357 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature