An Enhanced Rule-based Expert System for Typhoid Fever Diagnosis using Fuzzy Logic

Abstract

This study deals with the design and development of a rule based expert system for diagnosis of typhoid fever, a common health disorder among Africans. This system interacts with users with plain English language based on some arranged rules. These rules, which are a typical collection of if/then rules, are extracted from experts in the medical fields in Nigeria. Using these rules, a knowledge base was designed for the expert system. Some programming codes were also written in PHP programming language for making deduction of new facts from rules in the knowledge base. The obtained results of the study showed that the proposed system outperforms the existing system in diagnostic speed and symptom processing. The evaluated parameters of the proposed system obtained values of 54 seconds and 45 seconds respectively for diagnostic speed and symptom processing when compared to the existing system which had values of 67 seconds and 84 seconds respectively. It is believed that this design can help to reduce the congestion we often see in our hospitals by providing solution for sick patients, irrespective of their locations.

Keywords

Diagnosis Fuzzy-Logic Improved Symptoms Typhoid Fever.

  • Research Identity (RIN)

  • License

    Attribution 2.0 Generic (CC BY 2.0)

  • Language & Pages

    English, 57-70

  • Classification

    I.5.1