Energy Efficient Data Mining Approach for Estimating the Diabetes

Abstract

Diabetes is a major cause of organ failure in the human body, and it is one of the leading causes of organ failure. As of now, there is no preventive medicine or vaccine for diabetes. As a result, people all around the world are accustomed to living with diabetes for the rest of their lives. Medical practitioners advise diabetic patients to have a healthy lifestyle that includes regular exercise and a well-balanced diet in order to prevent the effects of diabetes from spreading to other organs of the human body. In most cases, the diabetes is spreading like a heredity disease to the infected people and even to children and it can’t be estimated priory. In recent days, the deep learning algorithms are widely used to estimate the forthcoming effects of several problems by using the data mining process. In the proposed work, the performance of deep ANN and back propagation ANN is considered for estimating diabetes from several primary data factors obtained from a publicly available dataset called Pima Indian diabetes dataset.