Prediction of Diabetes Using Machine Learning and Deep Learning Approaches: A Survey

Abstract

One of the most prevalent and severe illnesses in the world today is diabetes. In addition to being bad for the blood, it also leads to several illnesses that kill many people each year, including blindness, kidney problems, and heart problems. Therefore, a system that can precisely identify people with diabetes utilizing their medical information needs to be developed. Numerous traditional methods exist for monitoring the health of people with diabetes. Patients must attend a diagnostic facility, speak with their doctor, and wait for some time to get the findings of the typical screening process. While several techniques have been developed over the last few years to identify diabetes, approaches such as machine learning (ML) and deep learning (DL) provide more informative outcomes. This paper reviewed all diabetes predictions based on ML and DL approaches. Furthermore, to create optimal solutions for diabetes detection and prediction, this study emphasizes the difficulties and potential avenues for future research in this field.