Performance of a Deep-Learning Algorithm vs Manual Grading for Detecting Diabetic Retinopathy in India.

ABSTRACT:

Importance

More than 60 million people in India have diabetes and are at risk for diabetic retinopathy (DR), a vision-threatening disease. Automated interpretation of retinal fundus photographs can help support and scale a robust screening program to detect DR.

Objective

To prospectively validate the performance of an automated DR system across 2 sites in India.

Design, setting, and participants

This prospective observational study was conducted at 2 eye care centers in India (Aravind Eye Hospital and Sankara Nethralaya) and included 3049 patients with diabetes. Data collection and patient enrollment took place between April 2016 and July 2016 at Aravind and May 2016 and April 2017 at Sankara Nethralaya. The model was trained and fixed in March 2016.

Interventions<

SUBMITTER: Gulshan V 

PROVIDER: S-EPMC6567842 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature