A web based decision support system driven by fuzzy logic for the diagnosis of typhoid fever

  • Authors:

  • O. W. Samuel;M. O. Omisore;B. A. Ojokoh

  • Affiliations:

  • Department of Computer Science, Federal University of Technology Akure, P.M.B. 704, Akure, Nigeria;Department of Computer Science, Federal University of Technology Akure, P.M.B. 704, Akure, Nigeria;Department of Computer Science, Federal University of Technology Akure, P.M.B. 704, Akure, Nigeria

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2013

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Abstract

Research has identified Typhoid Fever (TF) as the major cause of morbidity and mortality in most developing countries. The diagnosis of TF involves several variables which usually makes it difficult to arrive at accurate and timely diagnosis. This research proposes a Web-Based Decision Support System (WBDSS) driven by Fuzzy Logic (FL) for the diagnosis of TF. The system comprises of a Knowledge Base (KB) and a Fuzzy Inference System (FIS).The FIS is composed of a Fuzzifier, Fuzzy Inference Engine (FIE), and a Defuzzifier. The FIE is the core of the FIS and it adopts the Root Sum Square (RSS) technique in drawing valid conclusion. The Fuzzifier uses a triangular membership function to determine the degree of contribution of each decision variable while the Defuzzifier adopts the Centroid of Area (CoA) defuzzification technique to generate a crisp output for a given diagnosis. An experimental study of the proposed system was conducted using medical records of TF patients obtained from the Federal Medical Center, Owo, Ondo State-Nigeria over a period of six months and the results of the study were found to be within the range of predefined limit as examined by medical experts. Standard statistical metrics were used to measure the efficiency of the proposed system and the results obtained show that the proposed system is 94% efficient in providing accurate diagnosis.