A Convolutional Neural Network Approach for Diabetic Retinopathy Classification
Nasmin Jiwani, Ketan Gupta, Neda Afreen
Abstract
Diabetic Retinopathy (DR) is a kind of problem which affects diabetic patients, particularly those at their age of working, and can result in vision impairment and possibly irreversible blindness. For diagnosis and to prevent blindness or degeneration, early detection is critical. When ophthalmologists execute the diagnosis step of DR manually, it takes more time, effort, and money, and there are more possibility of misdiagnosis. The scientific community is focusing on developing a computer-aided recognition system for early identification and grading of DR severity. Ongoing AI research has highlighted the growth of the deep learning technique, which is better technique for doing medical image analysis and classification.