Diagnosis of Diabetes using Artificial Neural Network and Neuro-Fuzzy approach

A main problem in diabetes is its timely and accurate diagnosis. This study aimed at diagnosing diabetes using data mining methods. The present study is an analytical investigation including 768 individuals with 8 attributes. Artificial neural networks and fuzzy neural networks were used to diagnose the diabetes. To achieve a realaccuracy, the Kfold method was used to divide samples into training and test groups. The mean square errors in multilayer perceptron network (MLP), learning vector quantization and Nero fuzzy networks were 98.6%, 98.2% and 99.6%, respectively. According to the results of this study, , data mining method can be effective in diagnosing diabetes. In this regard, both used methods are useful; however, higher precision was obtained following the use of Neuro-Fuzzy approach.