A Rule Based Neuro-Fuzzy Expert System Model for Diagnosis of Diabetes

E. Sreedevi, Prof.M. Padmavathamma


In the field of artificial intelligence, neuro-fuzzy system is a combination of artificial neural networks and fuzzy logic. Diabetes is a serious, life-threatening, chronic disease which occurs when your body does not produce enough insulin or cannot use the insulin it produces. Identifying the disease accurately depends on the method that is used in diagnosing disease. An enhanced approach for diagnosis of diabetes is to create an expert system with Artificial Neural Networks that has artificial intelligence characteristics. There are number of approaches available. One such approach is by the use of a combination of rule based, neural networks and fuzzy logic to create a Neuro-Fuzzy Expert System (NFES). By means of NFES, diagnosis of diabetes becomes simple for medical practitioners/physicians. This paper will discuss the design & proposed model involved in creating such a NFES system to diagnose diabetes.


Keywords: Neuro-fuzzy system, Fuzzy logic, feed forward architecture, Expert System, Diabetes

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DOI: https://doi.org/10.26483/ijarcs.v5i8.2381


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