An Expertise System for Insulin Dosage Prediction using Machine Learning Techniques

Abstract: Diabetes Mellitus is a chronic metabolic disorder. Normally, with a proper adjusting of blood glucose levels (BGLs), diabetic patients could live a normal life without the risk of having serious complications that normally developed in the long run. However, blood glucose levels of most diabetic patients are not well controlled for many reasons. Although the traditional prevention techniques such as eating healthy food and conducting physical exercise are important for the diabetic patients to control their BGLs, however taking the proper amount of insulin dosage has the crucial rule in the treatment process. In this project we are using Gradient Boosting Classifier to predict diabetes and then using Linear Regression algorithm to predict insulin dosage in diabetis detected patients. To implement this project we are using PIMA diabetes dataset and UCI insulin dosage dataset. We are training both algorithms with above mention dataset and once after training we will upload test dataset with no class label and then Gradient Boosting will predict presence of diabetes and Linear Regression will predict insulin dosage if diabetes detected by Gradient Boosting.

Keywords: Diabetis Mellitus, Blood Glucose Levels (BGLs), Insulin Dosage, Gradient Boosting Classifier, Linear Regression.