Mobile-Based Fuzzy Expert System for Diagnosing Malaria (MFES)

Malaria is a deadly disease that claims yearly lives of millions in Africa, and other endemic continents. The prevalence of malaria in these endemic regions is majorly attached to the lack of competent medical experts who are capable of providing medical care for the affected victims. This study considers developing a mobile based fuzzy expert system that could assist in diagnosing malaria. The fuzzification of crisp inputs by the system was carried out using an inter-valued and triangular membership functions while the deffuzification of the inference engine outputs was performed by weighted average method. Root sum square method of drawing inferences has been employed while the whole development has been achieved with the help of Java 2 Micro Edition of Java. This expert system executes on the readily available mobile devices of the patients. This fuzzy system was finally evaluated and confirmed effective in providing a human-expert like diagnosis.