An Expert System For Malaria Management Using Fuzzy Logic

ABSTRACT

Malaria has been identified as a significant threat to human life, resulting in millions of deaths each year and hindering economic progress. Many countries, especially in Africa and Asia, invest considerable resources and time to combat the disease. The high mortality rate associated with malaria has often been attributed to the shortage of medical professionals, hospitals, and essential equipment. Despite ongoing research in this field, challenges remain due to information, economic, and educational limitations, as well as insufficient feedback from medical experts at all levels of healthcare. Accurate diagnostic models, particularly for vulnerable pregnant women and children in temperate regions, are essential to match the diagnostic capabilities of physicians. This study aimed to design and implement a system to aid in the diagnosis, prediction, and treatment of malaria using fuzzy logic. PHP was used for scripting, MySQL for the database, and Apache served as the server for the inference engine. Primary data was collected by distributing 32 research questionnaires in Specialist Hospital Gashua and General Hospitals Nguru and Yusufari in Yobe state North-eastern Nigeria, with a sample size of 30 patients. Fuzzy logic was utilized for data analysis, revealing that Patient number 001 had an 81.0% probability of severe malaria. The study concluded that fuzzy logic was highly effective in predicting and diagnosing malaria and provided valuable recommendations for the hospitals involved.

Keywords: Fuzzy Logic, Expert System, Malaria.