Validation of a Deep Learning Model for Diabetic Retinopathy on Patients with Young-Onset Diabetes.

ABSTRACT:

Introduction

While many deep learning systems (DLSs) for diabetic retinopathy (DR) have been developed and validated on cohorts with an average age of 50s or older, fewer studies have examined younger individuals. This study aimed to understand DLS performance for younger individuals, who tend to display anatomic differences, such as prominent retinal sheen. This sheen can be mistaken for exudates or cotton wool spots, and potentially confound DLSs.

Methods

This was a prospective cross-sectional cohort study in a "Diabetes of young" clinic in India, enrolling 321 individuals between ages 18 and 45 (98.8% with type 1 diabetes). Participants had fundus photographs taken and the photos were adjudicated by experienced graders to obtain reference DR grades. We defined a younger c

SUBMITTER: Tan-Torres A 

PROVIDER: S-EPMC12006647 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature