This paper expresses the prominent futures of fuzzy expert system by applying the algorithm T Fuzzy Assessment Methodology. Fuzzy expert system consists of the following elements such as fuzzification interface, T Fuzzy Assessment Methodology, and defuzzification. T Fuzzy Assessment Methodology uses the K Ratio to find overlapping between membership function and T Fuzzy similarity measure the s...

In most Fuzzy System applications the structure of the system is chosen non-systematically by an expert according to his knowledge. Nevertheless the system parameters are rich enough to ensure the desired behavior. In the following, we introduce an automatic learning algorithm by de nition of a 1) well behaved and 2) minimal Fuzzy System. A Genetic Algorithm is used to estimate the Fuzzy System...

Gestational diabetes mellitus (GDM) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. One of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. This paper intends to propose an expert system in order to diagnose the risk of GDM by using FIS model. The knowl...

Soft Computing techniques play an important role for decision in applications with imprecise and uncertain knowledge. The application of soft computing disciplines is rapidly emerging for the diagnosis and prognosis in medical applications. Between various soft computing techniques, fuzzy expert system takes advantage of fuzzy set theory to provide computing with uncertain words. In a fuzzy exp...

Background: Medical practice is usually performed in a context of uncertainty, where expert knowledge has shown to be efficient in the decision-making process. Objective: The aim of this study was to develop and validate a fuzzy logic-based model to predict cardiac surgery mortality risk. Methods: Four hundred and fifty patients undergoing cardiac surgery were prospectively included in the stud...