Impute the Missing Data through Fuzzy Expert System for the Medical Data Diagnosis

Abstract

Data Processing with missing attribute values based on fuzzy sets theory. By matching attribute-value pairs among the same core or reduce of the original data set, the assigned value preserves the characteristics of the original data set. Malaria represents major public health problems in the tropics. The harmful effects of malaria parasites to the human body cannot be underestimated. In this paper, a fuzzy expert system for the management of malaria (FESMM) was presented for providing decision support platform to malaria researchers, The fuzzy expert system was designed based on clinical observations, medical diagnosis and the expert�s knowledge. We selected 15 cases with Malaria and computed the missing results that were in the range of common attribute element by the domain experts.