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Cognitive analysis of multiple sclerosis utilizing fuzzy cluster means

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Author(s): Imianvan Anthony Agboizebeta | Obi Jonathan Chukwuyeni

Journal: International Journal of Artificial Intelligence & Applications
ISSN 0976-2191

Volume: 3;
Issue: 1;
Start page: 33;
Date: 2012;
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Keywords: Fuzzy logic | Fuzzy Set | Fuzzy Cluster Means | Diagnosis | Multiple sclerosis | Membership Function

ABSTRACT
Multiple sclerosis, often called MS, is a disease that affects the central nervous system (the brain andspinal cord). Myelin provides insulation for nerve cells improves the conduction of impulses along thenerves and is important for maintaining the health of the nerves. In multiple sclerosis, inflammationcauses the myelin to disappear. Genetic factors, environmental issues and viral infection may alsoplay a role in developing the disease. Ms is characterized by life threatening symptoms such as; loss ofbalance, hearing problem and depression. The application of Fuzzy Cluster Means (FCM or Fuzzy CMean)analysis to the diagnosis of different forms of multiple sclerosis is the focal point of this paper.Application of cluster analysis involves a sequence of methodological and analytical decision stepsthat enhances the quality and meaning of the clusters produced. Uncertainties associated withanalysis of multiple sclerosis test data are eliminated by the system
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