Predictive Analytics on Diabetes Data using Machine Learning Techniques

Diabetes mellitus is an ongoing illness related with anomalous undeniable levels of the sugar glucose in the blood and it is a major public health problem. Diabetes has become the 4
^th
driving reason for death in developed countries. Though several methodologies have been developed to predict this chronic disease, there is a need for innovative approaches which may aid in early prediction of diabetes and its complications. This research work aims at developing an effective diabetes prediction system by taking advantage of machine learning. In this study, distinctive AI methods are applied to perform predictive analytics over the diabetes data sets. The proposed system strives for better prevention, diagnosis and management of Type 2 diabetes and focuses on developing machine learning strategies for precision medicine. It provides a platform not only for early recognition of Type 2 diabetes but also prevention of hazardous complications. The proposed system allows the practitioners to predict more precisely which treatment and prevention systems for diabetes will work as the best for specified patients. Thus, the system will greatly contribute to the quality of healthcare and beneficial to a large extent of today's community.