Identifying the Risk Factors for Diabetic Retinopathy Using Decision Tree

Abstract

The role of data mining in healthcare industry is to improve the health systems and to use these data analytics to identify the inefficiencies and to improve care. Accuracy is important when it comes to patient care, and handling this huge amount of data improves the quality of the healthcare system. Diabetic retinopathy is a disease mainly occurring in patients with high sugar level in their blood. The situation occurs when sugar levels in blood are high, thus causing damage to blood vessels. The blood vessels swell and leak and gradually affect the eye vision. This is not detected in early stage of diabetics, even though it affects the eyesight from the beginning. Decision tree classification helps to detect the problem in the initial stage that helps to find the risk factors that cause this disease. Better treatment is provided to those infected patients. A detailed analysis of the result from the decision tree classifier is also presented in this work, and decisive factors for diabetic retinopathy are concluded herewith.