A Fuzzy Expert System for Malaria Disease Detection

Abstract

It is found that the malaria disease is a prime and major cause to the human health. The pernicious trappings of malaria stooge to the physical body cannot be making light of it. In this research work, a fuzzy-based expert system for the total handling of malaria disease had granted for providing judgment support platform to the specialist and healthcare researchers in the same endemic province. The proposed and implemented system consists of major components which include the cognitive content, the fuzzification, the inference engine and de-fuzzification for decision making. The fuzzy inference engine developed during this work is that the root sum square. This method is the depiction of inference that was designed and developed to infer the info from the fuzzy-based rules used in this algorithm. Triangular fuzzy membership function was accustomed that shows the degree of attendance of every input specification, and therefore, the de-fuzzification technique employed during this research is that the centre of gravity. This fuzzy-based expert system had been developed to help and to support clinical perception, diagnosis and therefore the expert’s proficiency. For validation and empharical analysis, the data of thirty patients with malaria defection was used. The results that were calculated are within the range of that was predefined and predicted by the territory proficient.