Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

ABSTRACT:

Importance

A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of ROP to improve visual outcomes.

Objective

To develop a retinal image-based, multidimensional, automated, deep learning platform for ROP screening and validate its performance accuracy.

Design, setting, and participants

A total of 14 108 eyes of 8652 preterm infants who received ROP screening from 4 centers from November 4, 2010, to November 14, 2019, were included, and a total of 52 249 retinal images were randomly split into training, validation, and test sets. Four main dimensional independent classifiers were developed, in

SUBMITTER: Wang J 

PROVIDER: S-EPMC8100867 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature