Abstract
Diabetes is a chronic illness without a conclusive cure, and is the most common cause of amputations, blindness, and chronic kidney failure, and an important risk factor in heart problems. The only hope for these patients is through proper care. The main difficulty, regarding this dangerous and destructive illness, is not detecting it in time, and generally, a weakness in detection. Hence, implementation of a method that can help in the detection of this illness is an important step toward the prevention and control of this illness, especially in the early stages. In this article, using adaptive neural fuzzy inference system (ANFIS), we have attempted to predict this illness. The speed and the validity of the suggested algorithm is more than the other smart methods used. The method proposed in this article, with a 10% validity increase during training and a 5% validity increase during experimentation has a better performance than previous smart methods
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