Evaluation on Diabetes Care Using Machine Learning

Diabetes is a chronic condition defined by elevated blood sugar levels. Machine learning (ML) has become more and more applied in the prediction and management of diabetes. A significant public health issue, diabetes affects 425 million persons globally. Diabetes consequences like cardiovascular disease, renal failure, and blindness can be avoided or delayed with early diagnosis and effective care of the condition. Additionally, ML has been applied to increase the precision of diabetes diagnosis testing. For instance, when a neural network was used to analyze the results of an oral glucose tolerance test, the model outperformed conventional diagnostic techniques in terms of sensitivity and specificity. Additionally, ML has been used to personalize diabetic medication, track the progression of disease, and forecast the likelihood of complications.