Early Stage Prediction of Diabetes Risk Using Machine Learning

Abstract

Diabetes is one of the more fatal diseases in this world. Additionally, it is the reason behind a different range of disorders. For instance, blindness, urinary organ diseases, coronary failure, etc. Yet, while new technologies and scientific advancements have resulted in many diseases being cured around the world, some like diabetes can be prevented but not cured. Numerous data mining approaches, using techniques such as K-Nearest Neighbor Algorithm, Logistic Regression Algorithm, and Random Forest Algorithm, have been applied in this domain for the detection, prediction, and classification of diabetes. The aim of this paper is to develop an approach that predicts the early stages of diabetes.