Comparative Analysis of Diabetic Retinopathy Using Deep Learning Concepts

Abstract

Diabetic retinopathy is a complication of diabetes that affects the eyes. It is a progressive disease that occurs in stages, each of which is characterized by specific changes in the retina. It is caused by damage to the blood vessels in the retina, which is the light-sensitive part of the eye that sends visual signals to the brain. People with diabetes, especially those with poorly controlled blood sugar levels, are at risk of developing diabetic retinopathy. Over time, high blood sugar levels can cause the blood vessels in the retina to become damaged or blocked. This can lead to swelling, bleeding, and the growth of abnormal blood vessels in the retina, which can cause vision loss or even blindness. Symptoms of diabetic retinopathy may include blurry vision, floaters (spots in the field of vision), and difficulty seeing at night. However, many people with diabetic retinopathy may not have any symptoms at all in the early stages of the condition. Treatment for diabetic retinopathy may involve controlling blood sugar levels, blood pressure, and cholesterol levels, as well as laser treatment, injections, or surgery in more advanced cases. Regular eye exams are also recommended for people with diabetes to detect any early signs of diabetic retinopathy and prevent vision loss. Keywords: Diabetic Retinopathy; Deep Learning; Image processing; Convolution neural network