Precise Detection of Diabetic Retinopathy using CNN Models in Machine Learning

Worldwide, millions of individuals worldwide suffer from diabetes, a chronic illness. One of the primary effects of diabetes is diabetic retinopathy, which can lead to blindness if left untreated. Early diagnosis and treatment of diabetic retinopathy are necessary to prevent longterm damage to the eyes. In this paper, we analyse the most recent findings in the study of diabetes diagnosis based on retinopathy. We review the many imaging modalities that can be used to identify retinopathy, including fundus photography, optical coherence tomography, and fluorescein angiography. Furthermore, we explore the application of artificial intelligence and artificial intelligence methods for the automatic detection and categorization of diabetic retinopathy.