Analysis of Diabetes disease using Machine Learning Techniques: A Review

Abstract

Purpose: Diabetes is a type of metabolic disorder with a high level of blood glucose. Due to the high blood sugar, the risk of heart-related diseases like heart attack and stroke got increased. The number of diabetic patients worldwide has increased significantly, and it is considered to be a major life-threatening disease worldwide. The diabetic disease cannot be cured but it can be controlled and managed by timely detection. Artificial Intelligence (AI) with Machine Learning (ML) empowers automatic early diabetes detection which is found to be much better than a manual method of diagnosis. At present, there are many research papers available on diabetes detection using ML techniques. Method: This article aims to outline most of the literature related to ML techniques applied for diabetes prediction and summarize the related challenges. Results: It also talks about the conclusions of the existing model and the benefits of the AI model. After a thorough screening method, 74 articles from the Scopus and Web of Science databases are selected for this study. Conclusion: This review article presents a clear outlook of diabetes detection which helps the researchers work in the area of automated diabetes prediction.