FUZZY CLUSTER MEANS EXPERT SYSTEM FOR THE DIAGNOSIS OF TUBERCULOSIS

FUZZY CLUSTER MEANS EXPERT SYSTEM FOR THE DIAGNOSIS OF TUBERCULOSIS

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University of Benin

FUZZY CLUSTER MEANS EXPERT SYSTEM FOR THE DIAGNOSIS OF TUBERCULOSIS

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Abstract

Tuberculosis (TB) is a global public health problem of enormous dimension. Tuberculosis is usually associated with mycobacterium tuberculosis (the bacterium causing tuberculosis). TB is an infectious disease, transmitted and spread via aerosols (droplets from the mouth and respiratory tract) that are coughed, sneezed, or forcibly expelled from the body to the surrounding air. These droplets, when inhaled by a susceptible host, can infect a new person and, within weeks to months, the disease begins to develop within the infected person. The lungs are the primary site of infection. The disease can spread to almost any other organ such as: kidneys, bladder, bones, spine, liver, spleen and brain. TB symptoms are characterized by low grade fever, coughing, fatigue, and a loss of appetite. Later, hemoptysis (coughing up blood), may occur. The application of Fuzzy Cluster Means (FCM or Fuzzy C-Mean) analysis to the identification of different types of tuberculosis is the focal point of this paper. Application of cluster analysis involves a sequence of methodological and analytical decision steps that enhances the quality and meaning of the clusters produced. The uncertainties often associated with analysis of tuberculosis test data are eliminated by the proposed system.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

tonyvanni. . "FUZZY CLUSTER MEANS EXPERT SYSTEM FOR THE DIAGNOSIS OF TUBERCULOSIS". Global Journal of Computer Science and Technology GJCST Volume 11 (GJCST Volume 11 Issue 6).

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GJCST Volume 11 Issue 6

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST Classification FOR Code: 080299

080204

080108

Submission ReceivedFebruary 4, 2011
Peer Review Double Blind
Handling Editor
Accepted March 6, 2011
Published March 18, 2011

Version of record

v1.2

Issue date

April 17, 2011

Language

English

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Article Matrices

Total Score: 147

Country: Nigeria

Subject: Global Journal of Computer Science and Technology

Authors: Dr. Imianvan A.A., Obi J.C. (PhD/Dr. count: 1)

View Count (all-time): 177

Total Views (Real + Logic): 7603

Total Downloads (simulated): 447

Publish Date: 2011 03, Fri

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Total Views: 7.6K

Total Downloads: 447

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