Hassanien, A. E.,
"Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing",
Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, Berlin, Heidelberg, Springer-Verlag , 2009.
AboulElla, H., A. Abraham, J. F. Peters, and G. Schaefer,
"Rough Sets in Medical Informatics Applications",
Applications of Soft Computing - Advances in Intelligent and Soft Computing, pp 23-30, Berlin , Springer Berlin Heidelberg (ISSN: 978-3-540-89618-0), 2009.
AbstractRough 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.
El-Dahshan, E. - S. A., A. E. Hassanien, A. Radi, and S. Banerjee,
"Ultrasound Biomicroscopy Glaucoma Images Analysis Based on Rough Set and Pulse Coupled Neural Network",
Foundations of Computational Intelligence, Volume 2, pp. 275-293 , London, Springer , 2009.
AbstractThe objective of this book chapter is to present the rough sets and pulse coupled neural network scheme for Ultrasound Biomicroscopy glaucoma images analysis. To increase the efficiency of the introduced scheme, an intensity adjustment process is applied first using the Pulse Coupled Neural Network (PCNN) with a median filter. This is followed by applying the PCNN-based segmentation algorithm to detect the boundary of the interior chamber of the eye image. Then, glaucoma clinical parameters have been calculated and normalized, followed by application of a rough set analysis to discover the dependency between the parameters and to generate set of reduct that contains minimal number of attributes. Finally, a rough confusion matrix is designed for discrimination to test whether they are normal or glaucomatous eyes. Experimental results show that the introduced scheme is very successful and has high detection accuracy.
Kudelka, M., V. Snásel, Z. Horak, and A. E. Hassanien,
"From Web Pages to Web Communities",
Annual International Workshop on DAtabases, TExts, Specifications and Objects, Spindleruv Mlyn, Czech Republic , April 15-17, 2009.
Abstract In this paper we are looking for a relationship between the intent of Web pages, their architecture and the communities who take part in their usage and creation. From our point of view, the Web page is entity carrying information about these communities and this paper describes techniques, which can be used to extract mentioned information as well as tools usable in analysis of these information. Information about communities could be used in several ways thanks to our approach. Finally we present an experiment which illustrates the benefits of our approach.
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