Automated Diagnosis of Diabetic Retinopathy using Deep Learning and Image Analysis - Kolli, Sujeeth Babu; Kalisetti, Vinay; Varaparla, Rakesh; Chandra Vasarla, Vamsi Sai; Ammisetty, Veeraswamy (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Diabetic Retinopathy (DR) is a significant cause of blindness and one of the principal complications of diabetes. For proper management and therapy, early identification and precise assessment of DR intensity levels are critical. In this paper, we present an automated identification approach based on deep learning and visual analysis technology. We categorize fundus photos using a convolutional neural network (CNN) based on the strength of their DR. Our strategy involves altering the photographs, constructing a good CNN design, and utilizing a massive dataset to train the model. The findings indicate how effectively our technology works to detect actual drug leftovers.