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Evaluation of the feature space of an erythematosquamous dataset using rough sets

Revett, Kenneth and Gorunescu, Florin and Salem, Abdel-Badeeh M. and El-Dahshan, El-Sayed (2009) Evaluation of the feature space of an erythematosquamous dataset using rough sets. Annals of the University of Craiova - Mathematics and Computer Science Series, 36 (2). pp. 123-130. ISSN 1223-6934

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Official URL: http://inf.ucv.ro/~ami/index.php/ami/article/view/...

Abstract

The differential diagnosis of erythematosquamous diseases remains a diffcult task requiring both clinical and histopathological data to support a diagnosis. The principle reason for diagnostic ambiguity is based on the significant degree of overlap in the overt symptoms of this class of disease. Histopathological evidence can assist in making a positive diagnosis - but is labor and resource intensive. In order to evaluate the diagnostic veracity of clinical versus histopathological features of erythematosquamous diseases, a comparison of both features classes was evaluated using rough sets. The results indicate that the histopathological feature space provided a much more significant classification rate relative to clinical features. In addition, the results of this preliminary study indicate that only a small subset of the histopathological feature space is required for maximal classiffication accuracy.

Item Type:Article
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:7098
Deposited On:06 Jan 2010 10:41
Last Modified:06 Jan 2010 10:41

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