Classification and Prediction of Diabetes Disease Using Modified k-neighbors Method

Digitalization in medicine has become one of the largest gaps in almost all healthcare systems in the world. Diabetes remains one of the pressing health problems. According to World Health Organization, the number of people with diabetes increased from 108 million in 1980 to 422 million in 2014. This research is devoted to solving the problem of classifying patients with diabetes and diagnosing this disease. To solve the problem, a machine learning model was built based on a modified k-nearest neighbors method. To develop the model, an open database of patients with diabetes, consisting of 768 patients, was used. The constructed model shows an accuracy of 89%. On the basis of the constructed model, a software package in the Python language has been developed.