Artificial Intelligence to Stratify Severity of Age-Related Macular Degeneration (AMD) and Predict Risk of Progression to Late AMD.

ABSTRACT:

Purpose

To build and validate artificial intelligence (AI)-based models for AMD screening and for predicting late dry and wet AMD progression within 1 and 2 years.

Methods

The dataset of the Age-related Eye Disease Study (AREDS) was used to train and validate our prediction model. External validation was performed on the Nutritional AMD Treatment-2 (NAT-2) study.

First step

An ensemble of deep learning screening methods was trained and validated on 116,875 color fundus photos from 4139 participants in the AREDS study to classify them as no, early, intermediate, or advanced AMD and further stratified them along the AREDS 12 level severity scale. Second step: the resulting AMD scores were combined with sociodemographic clinical data and other automatically extracted ima

SUBMITTER: Bhuiyan A 

PROVIDER: S-EPMC7396183 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature