Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/94687
Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Informatika / Computer science (N009)
Author(s): Marcinkevičius, Virginijus;Bernatavičienė, Jolita;Dzemyda, Gintautas;Kurasova, Olga
Title: Decision support for preliminary medical diagnosis integrating the data mining methods
Is part of: Simulation and optimisation in business and industry: international conference on operational research, May 17-20, 2006 Tallinn, Estonia. Kaunas : Technologija, 2006
Extent: p. 155-160
Date: 2006
ISBN: 9955250615
Abstract: In this paper, we investigate the human physiological data that describe the human functional state. Some physiological features are measured by changing the physical load. Two groups are analysed: sportsmen and ischemic heart-diseased men. The multidimensional data, are formed from the parameters of the physiological features. These data are classified using support vector machine (SVM). When the data are classified, it is important to determine so called the decision surface that divides the data into two classes. It is impossible to comprehend the decision surfaces in the n-dimensional space (n > 3). So, we propose to project the multidimensional data on to a plane, and then to determine the decision surfaces in two-dimensional space. To make a preliminary diagnosis of the new patient, it suffices to map the point, corresponding to this patient, among the previously mapped points. A decision on the possible health troubles is made via a visual analysis of the position of the point in respect of the decision surfaces
Internet: https://hdl.handle.net/20.500.12259/94687
Affiliation(s): Matematikos ir informatikos institutas
Vytauto Didžiojo universitetas
Švietimo akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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