Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.

ABSTRACT:

Importance

A deep learning system (DLS) is a machine learning technology with potential for screening diabetic retinopathy and related eye diseases.

Objective

To evaluate the performance of a DLS in detecting referable diabetic retinopathy, vision-threatening diabetic retinopathy, possible glaucoma, and age-related macular degeneration (AMD) in community and clinic-based multiethnic populations with diabetes.

Design, setting, and participants

Diagnostic performance of a DLS for diabetic retinopathy and related eye diseases was evaluated using 494 661 retinal images. A DLS was trained for detecting diabetic retinopathy (using 76 370 images), possible glaucoma (125 189 images), and AMD (72 610 images), and performance of DLS was evaluated for detecting diabetic retinopa

SUBMITTER: Ting DSW 

PROVIDER: S-EPMC5820739 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature