Sangeeta Waren, Nitesh Dubey
Diabetes Mellitus is critical and many people suffer from this condition. Diabetes mellitus may be the cause of age, obesity, lack of exercise, genetic diabetes, lifestyle, poor diet, high blood pressure, etc. Diabetes people have a high risk of heart failure, kidney disease, stroke, eye problem, nerve damage, etc. Current in-hospital procedure is to obtain the requisite diabetes diagnostic information through numerous tests and proper diagnostic care. In the healthcare sectors, big data analytics plays an important role. Healthcare industries have extensive databases. Big data analytics allow you to research large datasets to find hidden information, hidden trends to detect knowledge from the data and to forecast results accordingly. The classification and prediction accuracy in the current system is not so high. In this paper we have presented a model predicting diabetes for a better diabetes classification, including few external diabetes factors and common factors such as Glucose, BMI, age, insulin, etc. The accuracy of classification is increased with new datasets relative to existing datasets. In addition, a diabetes prediction pipeline model has been imposed to improve classification accuracy.
Diabetes Mellitus, Big Data Analytics, Healthcare Machine Learning.