Nephropathy forecasting in diabetic patients using a GA-based type-2 fuzzy regression model

Choosing a proper method to predict and timely prevent the complications of diabetes could be considered a significant step toward optimally controlling the disease. Since in medical research only small sample sizes of data are available and medical data always includes high levels of uncertainty and ambiguity, a type-2 fuzzy regression model seems to be an appropriate procedure for finding the relationship between outcome and explanatory variables in medical decision-making. In this paper, a new type-2 fuzzy regression model based on type-2 fuzzy time series concepts is used to forecast nephropathy in diabetic patients. Results in two examples show model efficiency. The use of such models in diabetes clinics is proposed.