A Nioetric Approach for Diabetes Detection

The main objective is to predict the glucose levels of patients. Blood Glucose level is the concentration of glucose present in the blood of humans. Diabetes is a chronic illness characterized by the absence of glucose. Insulin therapy is needed to maintain Blood Glucose levels in the advised target range. According to global report on diabetes by World Health Organization, over 400 million people suffer from diabetes. Regular monitoring of Blood Glucose Level is of paramount importance in the treatment process. Diabetes can be found out in many ways. We use Machine Learning algorithms to predict whether the patient has diabetes or not. The algorithms like Logistic regression, Support vector machine, Artificial neural networks and Deep learning neural network are used to predict the chances of diabetes of a patient. First we take some parameters of patient which include blood pressure, sex, diabetes pedigree function, BMI, age, Insulin, skin thickness etc. Then by giving these features input to the machine learning algorithms we can predict the blood glucose level of the patient. At last we compare the output produced by four machine learning algorithms