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Prediction of coronary arteriosclerosis in stable coronary heart disease

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dc.contributor.author Bazan, Jan. G.
dc.contributor.author Bazan-Socha, Stanisława
dc.contributor.author Buregwa-Czuma, Sylwia
dc.contributor.author Pardel, Przemysław W.
dc.contributor.author Sokolowska, Barbara
dc.date.accessioned 2014-11-14T17:40:30Z
dc.date.available 2014-11-14T17:40:30Z
dc.date.issued 2012
dc.identifier.citation Praca opublikowana jako: Bazan, J., G., Bazan-Socha, S., Buregwa-Czuma, S., Pardel, P., Sokolowska, B.: Prediction of coronary arteriosclerosis in stable coronary heart disease, In S. Greco, B. Bouchon-Meunier, G. Coletti, M. Fedrizzi, B. Matarazzo, and R. R. Yager (Eds.), Advances in Computational Intelligence , volume 298 of Communications in Computer and Information Science, pages 550-559. Springer, 2012. Oryginalna publikacja jest dostępna na stronie www.sprigerlink.com (The original publication is available at www.sprigerlink.com).
dc.identifier.uri http://repozytorium.ur.edu.pl/handle/item/669
dc.description pl_PL.UTF-8
dc.description.abstract The aim of the study was to assess the usefulness of classification methods in recognizing cardiovascular pathology. From the medical point of view the study involves prediction of coronary arteriosclerosis presence in patient with stable angina using clinical data and electrocardiogram (ECG) Holter monitoring records. On the grounds of these findings the need for coronary interventions is determined. An approach to solving this problem has been found in the context of rough set theory and methods. Rough set theory introduced by Zdzislaw Pawlak during the early 1980s provides the foundation for the construction of classifiers. From the rough set perspective, classifiers presented in the paper are based on a decision tree calculated on the basis of the local discretization method. The paper includes results of experiments that have been performed on medical data obtained from II Department of Internal Medicine, Jagiellonian University Medical College, Krakow, Poland. pl_PL.UTF-8
dc.description.sponsorship This work was supported by the grant N N516 077837 from the Ministry of Science and Higher Education of the Republic of Poland, the Polish National Science Centre (NCN) grant 2011/01/B/ST6/03867 and by the Polish National Centre for Research and Development (NCBiR) grant No. SP/I/1/77065/10 in frame of the the strategic scientific research and experimental development program: ``Interdisciplinary System for Interactive Scientific and Scientific-Technical Information''. pl_PL.UTF-8
dc.language.iso eng pl_PL.UTF-8
dc.publisher Springer-Verlag pl_PL.UTF-8
dc.subject rough sets pl_PL.UTF-8
dc.subject discretization pl_PL.UTF-8
dc.subject classifiers pl_PL.UTF-8
dc.subject stable angina pectoris pl_PL.UTF-8
dc.subject morbus ischaemicus cordis pl_PL.UTF-8
dc.subject ECG Holter pl_PL.UTF-8
dc.title Prediction of coronary arteriosclerosis in stable coronary heart disease pl_PL.UTF-8
dc.type conferenceObject pl_PL.UTF-8


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