تشخیص بیماری دیابت با استفاده از شبکه عصبی مصنوعی و عصبی- فازی

Background & Aim: A main problem in diabetes is its timely and accurate diagnosis. This study aimed at diagnosing diabetes using data mining methods. 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 real accuracy, the Kfold method was used to divide samples into training and test groups. Results: 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. Conclusion: 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.