A Review of the Research to Detect Diabetic Retinopathy Using Deep Learning

Diabetes, a most prevalent disease that affects peoples of all ages and is caused by inadequate insulin production, which raises blood sugar levels. Several diseases can develop throughout the body if treatable conditions are not addressed. Diabetes causes diabetic retinopathy (DR), an asymptomatic eye condition which affects retinal blood vessels. In this paper, numerous automated diagnosis systems have been created using Deep Learning technique. Deep Learning (DL) performs autonomous feature extraction, which enables it to produce more accurate and promising results, particularly for medical data. The most often used deep learning methods for processing medical image data are convolutional neural networks (CNN). This research analyses and discusses several Deep Learning-based Convolutional Neural Network, Support Vector Machine (SVM) models for diagnosing and classifying diabetic retinopathy with further literature reviews and classification in order to acquire a better knowledge of the condition.