Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals

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  • Additional Information
    • Publication Information:
      Department of Microelectronics & Computer Science
    • Publication Date:
      2020
    • Abstract:
      CardioTocoGraphic (CTG) monitoring is the primary method of fetal condition assessment. Due to the inter- and intra-observer disagreement between experts when evaluating signals visually, a well established solution supporting the diagnostic decision is automated classification of CTG signals. The goal of this paper is to propose a method of simplifying the fuzzy classifier rule base by combining ε-similar rules, to achieve high quality of CTG signals classification, but with fewer conditional rules. The results of experiments performed using the benchmark CTG database confirm the efficiency of the introduced method.
    • Contents Note:
      Conference Acronym: MIXDES
    • Author Affiliations:
      Silesian University of Technology,Department of Cybernetics, Nanotechnology and Data Processing,Gliwice,Poland
      Łukasiewicz Research Network – Institute of Medical Technology and Equipment,Zabrze,Poland
      VSB – Technical University of Ostrava,Ostrava,Czech Republic
    • ISBN:
      978-83-63578-17-6
      978-83-63578-18-3
    • Relation:
      2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES)
    • Rights:
      Copyright 2020, Department of Microelectronics & Computer Science
    • AMSID:
      9156069
    • Conference Acronym:
      MIXDES
    • Date of Current Version:
      2020
    • Document Subtype:
      IEEE Conference
    • Notes:
      Conference Location: Wroclaw, Poland, Poland

      Conference Start Date: 25 June 2020

      Conference End Date: 27 June 2020
    • Accession Number:
      edseee.9156069
  • Citations
    • ABNT:
      JEZEWSKI, M. et al. Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals. 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference on, [s. l.], p. 213–217, 2020. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069. Acesso em: 25 nov. 2020.
    • AMA:
      Jezewski M, Czabanski R, Leski JM, Matonia A, Martinek R. Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals. 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference on. June 2020:213-217. Accessed November 25, 2020. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069
    • APA:
      Jezewski, M., Czabanski, R., Leski, J. M., Matonia, A., & Martinek, R. (2020). Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals. 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference On, 213–217.
    • Chicago/Turabian: Author-Date:
      Jezewski, Michal, Robert Czabanski, Jacek M. Leski, Adam Matonia, and Radek Martinek. 2020. “Combining ε-Similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals.” 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference On, June, 213–17. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069.
    • Harvard:
      Jezewski, M. et al. (2020) ‘Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals’, 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference on, pp. 213–217. Available at: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069 (Accessed: 25 November 2020).
    • Harvard: Australian:
      Jezewski, M, Czabanski, R, Leski, JM, Matonia, A & Martinek, R 2020, ‘Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals’, 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference on, pp. 213–217, viewed 25 November 2020, .
    • MLA:
      Jezewski, Michal, et al. “Combining ε-Similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals.” 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference On, June 2020, pp. 213–217. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069.
    • Chicago/Turabian: Humanities:
      Jezewski, Michal, Robert Czabanski, Jacek M. Leski, Adam Matonia, and Radek Martinek. “Combining ε-Similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals.” 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference On, June 1, 2020, 213–17. http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069.
    • Vancouver/ICMJE:
      Jezewski M, Czabanski R, Leski JM, Matonia A, Martinek R. Combining ε-similar Fuzzy Rules for Efficient Classification of Cardiotocographic Signals. 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES), Mixed Design of Integrated Circuits and System (MIXDES), 2020 27th International Conference on [Internet]. 2020 Jun 1 [cited 2020 Nov 25];213–7. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.9156069