Prevention of Diabetes Using Data Mining Techniques

Diabetes is one of the major health issues among youngsters nowadays because of poor diet, family history, lifestyle habits. The medical diagnosis is important based on complicated risks that should be performed accurately and effectively. Based on the result and reports further investigation is needed through diagnosis and treatment are given to the patient. Many numbers of the data can be available in the healthcare systems. The availability and necessary medical data can be analyzed for data analysis tools to extract useful information through pattern recognition. Both data mining and knowledge discovery data are infinite applications including business and research scientific fields. Diabetes is one of the major applications nowadays where data mining tools are very useful to easily diagnose and find the solution. This paper, diagnoses diabetes through data mining tools such as SVM, association rule, clustering, and association. So, Data mining helps to predict and diagnose diseases with a low occurrence of risks. In this paper, the main focus is to make a present detailed survey of various data mining techniques and approaches that have been put to use for the prognosis of diabetes.