Comparing three data mining algorithms for Identifying the associated risk factors of type 2 diabetes

ABSTRACT

Background: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to identify the risk factors associated with type 2 diabetes. In this light, artificial neural network [ANN], support vector machines [SVMs], and multiple logistic regression [MLR] models were applied, using demographic, anthropometric, and biochemical characteristics, on a sample of 9528 individuals from Mashhad City in Iran