Published Paper Details:

Diabetes Mellitus is among the critical diseases and many people are suffering from this disease. Age, obesity, lack of exercise, hereditary diabetes, lifestyle, bad diet, high blood pressure, etc., can cause Diabetes Mellitus. People with diabetes have a high risk of diseases like heart disease, kidney disease, stroke, eye problem, nerve damage, etc. Current practice in hospital is to collect required information for diabetes diagnosis through various tests and appropriate treatment is provided based on diagnosis. Big Data Analytics plays an significant role in healthcare industries. Healthcare industries have large volume databases. Using big data analytics one can study huge datasets and find hidden information, hidden patterns to discover knowledge from the data and predict outcomes accordingly. In existing method, the classification and prediction accuracy is not so high. In this paper, we have proposed a diabetes prediction model for better classification of diabetes which includes few external factors responsible for diabetes along with regular factors like Glucose, BMI, Age, Insulin, etc. Classification accuracy is boosted with the new dataset compared to the existing dataset. Further, a pipeline model for diabetes prediction was imposed, intended to improve classification accuracy.