Data Mining in Healthcare for Diabetes Mellitus

Disease diagnosis is one of the applications where data mining tools are proving successful results. Diabetes disease is the leading cause of death all over the world in the past years. Several researchers are using statistical data. The availability of huge amounts of medical data leads to the need for powerful mining tools to help health care professionals in the diagnosis of diabetes disease. Using data mining technique in the diagnosis of diabetes disease has been comprehensively investigated, showing the acceptable levels of accuracy. Recently researchers have been investigating the effect of hybridizing more than one technique showing enhanced results in the diagnosis of diabetes disease. However, using data mining techniques to identify a suitable treatment for diabetes disease patients has received less attention. This paper identifies gaps in the research on diabetes disease diagnosis and treatment. It helps to systematically close those gaps to discover if applying data mining techniques to diabetes disease treatment data can provide as reliable performance as that achieved in controlling and diagnosing diabetes disease.