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Rough Sets in Medical Informatics Applications

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Applications of Soft Computing

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 58))

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.

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Hassanien, A.E., Abraham, A., Peters, J.F., Schaefer, G. (2009). Rough Sets in Medical Informatics Applications. In: Mehnen, J., Köppen, M., Saad, A., Tiwari, A. (eds) Applications of Soft Computing. Advances in Intelligent and Soft Computing, vol 58. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89619-7_3

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  • DOI: https://doi.org/10.1007/978-3-540-89619-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89618-0

  • Online ISBN: 978-3-540-89619-7

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