A Decision Support System Model for Diagnosing Tropical Diseases Using Fuzzy Logic

Malaria, Typhoid, Tuberculosis, Sexually Transmitted Diseases, Urinary Tract Infection, Yellow fever, Hepatitis-B, Leprosy and Chicken Pox are the existing tropical diseases that are considered in this work. In sub-Saharan Africa, the application of fuzzy logic to the diagnosis of these diseases is still very sparse and in some places practically nonexistent. Fuzzy set theory and fuzzy logic are very suitable and applicable basis for developing knowledge-based systems in medicine for diagnostic tasks. Our design demonstrate how information technology and medicine can successfully operate together using differential diagnosis by applying fuzzy logic to medical informatics We verified our approach with trials with the following systems which are: A fuzzy expert system for syndromes differentiation in oriental traditional medicine, an expert system for lung diseases using fuzzy logic, case based reasoning for medical diagnosis using fuzzy set theory, a diagnostic system combining disease diagnosis of western medicine with syndrome differentiation of oriental traditional medicine, a fuzzy system for classification of western and eastern medications and a fuzzy system for diagnosis and treatment of integrated western and eastern medicine. Results from our experiments showed that fuzzy logic is known to resolve the conflicts arising from ambiguity, uncertainty and imprecision of information [1]. Keyword: Malaria, Fuzzy Logic, Medicine, System, Expert System.