Classification of Diabetic Retinopathy Disease Levels by Extracting Topological Features Using Graph Neural Networks

Abstract

Diabetic retinopathy (DR) is one of

the most common causes of blindness in the

world”. It has to be diagnosed quickly and

accurately so that treatment may begin as soon

as possible. Manual examination of fundus

photographs by doctors is prone to mistakes

and is labor-intensive. “Using computer-assisted

methods, especially Convolutional Neural

Networks (CNNs), to automate DR diagnosis

seems promising”.