Rough sets in medical informatics applications

Aboul Ella Hassanien, Ajith Abraham, James F. Peters, Gerald Schaefer

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

Rough sets offer an effective approach of managing uncertainties and can be employed for tasks such as data dependency analysis, feature identification, dimensionality reduction, and pattern classification. As these tasks are common in many medical applications it is only natural that rough sets, despite their relative 'youth' compared to other techniques, provide a suitable method in such applications. In this paper, we provide a short summary on the use of rough sets in the medical informatics domain, focussing on applications of medical image segmentation, pattern classification and computer assisted medical decision making.

Original languageEnglish
Title of host publicationAdvances in Intelligent and Soft Computing
PublisherSpringer
Pages23-30
Number of pages8
Volume58
ISBN (Print)9783540896180
DOIs
Publication statusPublished - 1 Jan 2009

Publication series

NameAdvances in Intelligent and Soft Computing
Volume58
ISSN (Print)18675662

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  • Cite this

    Hassanien, A. E., Abraham, A., Peters, J. F., & Schaefer, G. (2009). Rough sets in medical informatics applications. In Advances in Intelligent and Soft Computing (Vol. 58, pp. 23-30). (Advances in Intelligent and Soft Computing; Vol. 58). Springer. https://doi.org/10.1007/978-3-540-89619-7_3