Prediction of Retinopathy in Diabetic Affected Persons using Deep Learning algorithms

The worldwide incidence of diabetic retinopathy (DR) is increasing, and DR is still a major source of eyesight loss universally. Diabetic retinopathy is a small blood vessel side effect of type 2 diabetes. Diabetic retinopathy diagnosis is important for inhibiting blindness, but increasing diagnosis is difficult as there is vast increase in number of affected persons s effected with diabetes. Retinal diagnosis aids in the premature finding and cure of diabetic retinopathy. Appearing in many cases, DR is not diagnosed until there is threat to vision. Previous research has mainly focused on attempting to control one important threat factor, glucose level. Nearly 21% of new cases of type 2 diabetes affected persons s had a side effect of DR, while 70% of affected persons have prolonged history of diabetic retinopathy for 20 years were identified with diabetic retinopathy. To further enhance the diagnosis process, this research study has developed Deep DR, a technique that involves deep learning to diagnose all phases of diabetic retinopathy.