Diabetic Retinopathy Detection Using Machine Learning

Abstract

It is a disease of the retina initiated through poorly controlled diabetes. In addition to damaging the retina, Diabetic Retinopathy causes irreversible damage to the human eye. It must be detected early to prevent permanent vision loss. In this work, we consider the five stages of diabetic retinopathy, also including a healthy retina. We use APTOS 2019 Blindness Detection Diabetic Retinopathy to train our model. We implement multiple approaches for forecasting machine-learning models in five stages. This proposed model predicts the stage of diabetic retinopathy: This model best works for South Asian people because there is some variation in the retinal image of different e geographical locations of the people. This proposed system only identifies diabetic retinopathy. And not applicable to other retinal diseases. This project aims to classify the diabetic retinopathy stage using images of any size of the patient’s retinal fundus. The patient provides the retinal fundus image, and this program converts the image into the required size and predicts the stage of diabetic retinopathy. Also, other researchers can see the predictions of different models used in this project.