Intelligent means of using Fuzzy Logic to determine the severity of Listeriosis disease

Abstract

— Listeriosis is an uncommon bacterial infection that is potentially fatal in the foetus, in newborns and immune compromised adults. Although the number of reported cases may be small but the high death rate associated with this infection is a significant public health concern and the reported cases as presented in is worrisome. The objective of this study is to design an intelligent means of using Fuzzy Logic for determining the severity of Listeriosis disease; this will assist the medical practitioners in the process of early discovery of the disease and proffer necessary medications. Ladoke Akintola (LAUTECH), Osogbo, Nigeria was used for the research. To ensure the confidentiality of the information collected and the anonymity, international ethical standards were followed. We used 8 clinical symptoms and 2 types of listeriosis diseases as our dataset. The system is developed in an environment characterized by Microsoft XP Professional operating system, Microsoft Access Database Management System, Visual BASIC Application Language and Microsoft Excel. We also performed training, testing and validation. The correct classified records are stored in the knowledge base. Rule extraction with the correct classified data was also performed .