Artificial Intelligence Algorithm for Diabetes Detection: Systematic Literature Review

Abstract

The number of diabetes sufferers increases from year to year, both in terms of number of cases and prevalence. Adults with diabetes also have a two- to three-fold increased risk of heart attack and stroke. During pregnancy, diabetes that is not well controlled will increase the risk of fetal death and other complications. Considering the link between the risk of developing complications from diabetes and the effects of death caused by this disease, early detection of diabetes is important. One way to detect diabetes is to use Artificial Intelligence for Diabetes Detection. The purpose of this writing is to identify the development of Artificial Intelligence Algorithms for Diabetes Detection. This research uses a systematic literature review using Preferred Reporting Items for Systematic Reviews (PRISMA). The results of article screening and selection found 72 potential articles that met the inclusion criteria. The research results show that with earlier detection, someone can check diabetes earlier using the help of machine learning. Before carrying out further medical checks, if the classification results show that the person is diagnosed with diabetes. One way to detect diabetes is by utilizing an Artificial Intelligence algorithm with a better level of accuracy.