Web System for the Prediction of Type II Diabetes Based on Machine Learning

Diabetes is a chronic disease, which is characterized by high levels of glucose in the blood and by too little insulin production or when it cannot be used effectively. The number of people who develop type 1 diabetes is increasing every year, it usually appears in the childhood or youth, and can develop during the development of the fetus in the womb, feeding during the first years of life, etc. Regarding type 2 diabetes, it occurs mostly from forty years and people suffering from obesity or other chronic diseases. This work presents the development of a web system application to support the pre-diagnosis of type II diabetes, with a precision acceptable using classification machine learning algorithms. The detection and diagnosis process will be facilitated with the use of machine learning algorithms for this, a framework will be developed using information based on health databases to anticipate whether the patient presents symptoms of diabetes or not, providing a basic diagnosis to anticipate the level threat with greater accuracy.