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PeriodicalsComputer Science & Information Technology

Knowledge-Based Fuzzy Inference System for Sepsis Diagnosis

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Abstract & Overview

In this study, a Fuzzy Inference System is developed to create a knowledge-based for the diagnosis and detection of sepsis using Matlab's fuzzy logic toolbox.The FIS consists of expert-specified input membership functions, output membership function, and IF-THEN rules.To validate our system, we tested it with the domain (medical) expert knowledge by comparing its performance with at least 10 hypothetical scenarios.The KB-FIS gave good answers in 8/10 scenarios and generated rules for decision support.The answers are qualitatively correct but quantitatively small.The fuzzy inference system designed performs as well as the medical experts under controlled conditions.With the methodology used in this study, it is hoped that it can assist in enhancing the knowledge-base system for proper, effective and early diagnosis and detection of sepsis

Cite this record

Igodan Charles Efosa, Akwukwuma V. V. N (2013). Knowledge-Based Fuzzy Inference System for Sepsis Diagnosis. International Journal of Computational Science and Information Technology, 1(3), 1–7. https://doi.org/10.5121/ijcsity.2013.1301

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Efosa, I. C., & N, A. V. V. (2013). Knowledge-Based Fuzzy Inference System for Sepsis Diagnosis. International Journal of Computational Science and Information Technology, 1(3), 1–7. https://doi.org/10.5121/ijcsity.2013.1301
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