Published Paper Details:

According to the World Health Organization (WHO), the seventh major cause of human death in 2030 will be diabetes, which of course is a very severe disease and if not treated thoroughly and on time, can lead to critical problems, including death. Millions of people are affected by the disease. The risk of diabetes is increasing day by day and is found mostly in women than men. The diagnosis of diabetes is a tedious process. Diabetic retinopathy is a disease caused by uncontrolled chronic diabetes and it can cause complete blindness if not timely treated. Therefore early medical diagnosis of diabetic retinopathy and it medical cure is essential to prevent the severe side effects of diabetic retinopathy. Manual detection of diabetic retinopathy by ophthalmologist take plenty of time and patients need to suffer a lot at this time. So with improvement in science and technology it is made easy to predict the disease. The purpose is to diagnose whether the person is affected by diabetes or not using classification based machine learning technique. This paper reviews, classifies and compares the algorithms and techniques previously proposed in order to develop better and more effective algorithms.