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Samira Karabpour & Ahmad Jafarian

A New Artificial Intelligence Method for Prediction of Diabetes Type2

(Volume 85 - Année 2016 — Actes de colloques — Special edition)
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Open Access

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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

Keywords : adaptive neural fuzzy inference system, diabetes, fuzzy data, fuzzy inference system, neural network

To cite this article

Samira Karabpour & Ahmad Jafarian, «A New Artificial Intelligence Method for Prediction of Diabetes Type2», Bulletin de la Société Royale des Sciences de Liège [En ligne], Volume 85 - Année 2016, Actes de colloques, Special edition, 376 - 391 URL : https://popups.uliege.be/0037-9565/index.php?id=5420.

About: Samira Karabpour

Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran

About: Ahmad Jafarian

Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran, Jafarian5594@yahoo.com