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

Revett, Kenneth, Gorunescu, Florin, 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

Full text not available from this repository.
Official URL: http://inf.ucv.ro/~ami/index.php/ami/article/view/...


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
Subjects: University of Westminster > Science and Technology > Electronics and Computer Science, School of (No longer in use)
Depositing User: Miss Nina Watts
Date Deposited: 06 Jan 2010 10:41
Last Modified: 06 Jan 2010 10:41
URI: http://westminsterresearch.wmin.ac.uk/id/eprint/7098

Actions (login required)

Edit Item (Repository staff only) Edit Item (Repository staff only)