Diabetic Retinopathy Disease Level Classification via Topological Feature Extraction using Graph Structure

An innovative approach to improving DRD level classification is taken up in this study by using Graph Neural Networks (GNNs). The goal of this study is to improve the DRD classification accuracy by building networks using topological properties extracted from retinal pictures. This program aspires to provide a more accurate and comprehensive assessment of DRD levels by using GNNs, which are very adept at identifying intricate relationships in graph-structured data. Early intervention and tailored treatment programs will be better understood in light of the findings.