• DocumentCode
    3686710
  • Title

    Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem

  • Author

    Marcin Grochowina;Lucyna Leniowska

  • Author_Institution
    University of Rzeszó
  • fYear
    2015
  • Firstpage
    249
  • Lastpage
    254
  • Abstract
    The paper presents a concise report on the comparison of the classifiers k-NN and SVM in the case of a fuzzy classification of the arterio-venous fistula based on audio recordings. What has been used in the studies are the acoustic signals taken from both healthy patients as well as those diagnosed with the narrowing of a fistula in a mild and major degree of stenosis. In the publication there have been selected two features, each presenting one- time and frequency domain, which enable a quite clear depiction of the classification result. The aim of the study is to develop a solution enabling the detection of fistula´s pathologies at an early stage.
  • Keywords
    "Support vector machines","Blood","Frequency-domain analysis","Accuracy","Heart beat","Time-domain analysis","Training"
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Systems (FedCSIS), 2015 Federated Conference on
  • Type

    conf

  • DOI
    10.15439/2015F194
  • Filename
    7321449