Comparative Evaluation of Diabetic Retinopathy Diagnosis Using Fundus Imaging Techniques

People can get a variety of diseases, some of which have no known treatment. One or both eyes may be affected by diabetic retinopathy (DR), a condition that can cause vision issues and possibly irreversible blindness. This is a very complicated problem. However, as was the case in other research conducted at the AIIMS, early detection can greatly reduce the burden of vision loss with the appropriate treatment and precautions. Applying advanced models with various picture Kaggle datasets and suggesting a convolutional neural network (CNN) model of comparable performance is the primary aim of this research. Interestingly, our suggested model had a 80.46% accuracy rate on kaggle dataset. Finding potential enhancements and resolving the issues these approaches face are the goals.