IJCATR Volume 8 Issue 2

Fuzzy Model for Diagnosis of Bacterial Meningitis

Dr. Oye, N. D. , Thomas, L. L.
10.7753/IJCATR0802.1001
keywords : Bacterial; Diagnosis; Fuzzy Logic; Fuzzy Model; Meninggitis

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Over the years, medical field has been one of the different areas where Artificial Intelligence methods were used in order to automate and improve its efficacy and precision. Insufficiency of medical specialist, fatigue, diagnosis error and several level of uncertainties or imprecision in the diagnosis of diseases are some of the factors affecting medical health delivery. Delaying patients with serious diseases like Meningitis may lead to loss of life. There is need for a system that will complement the effort of the medical personnel. This research simulates a fuzzy model for the diagnosis of Bacterial Meningitis using MATLAB R2015a. Symptoms of Meningitis were collected from the domain expert as input to the system, Triangular membership function was used to indicate the degree of membership of each input variable, the type of inference used was Mamdani while for defuzzification, centroid defuzzification method was used. The output of the system is presented on a surface viewer. A mathematical model was also developed. This research was implemented using Microsoft visual studio 2015 and C# while MSSQL sever management studio 2012 was used for the knowledge base. The outcome of a diagnosis is either present or absent. Records of diagnosed patients are reported in a graphical form in three categories; By Location, Gender and Age for easy analysis.
@artical{d822019ijcatr08021001,
Title = "Fuzzy Model for Diagnosis of Bacterial Meningitis",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "8",
Issue ="2",
Pages ="33 - 57",
Year = "2019",
Authors ="Dr. Oye, N. D. , Thomas, L. L."}