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Intelligent Phonocardiography for Screening Ventricular Septal Defect Using Time Growing Neural Network
Department of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
CAPIS Biomedical Research and Development Center, Mon, Belgium.
Department of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Department of Information Science and Media Studies, University of Bergen, Norway.
2017 (English)In: Informatics Empowers Healthcare Transformation / [ed] Househ M.S.,Mantas J.,Hasman A.,Gallos P., IOS Press, 2017, Vol. 238, p. 108-111Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents results of a study on the applicability of the intelligent phonocardiography in discriminating between Ventricular Spetal Defect (VSD) and regurgitation of the atrioventricular valves. An original machine learning method, based on the Time Growing Neural Network (TGNN), is employed for classifying the phonocardiographic recordings collected from the pediatric referrals to a children hospital. 90 individuals, 30 VSD, 30 with the valvular regurgitation, and 30 healthy subjects, participated in the study after obtaining the informed consents. The accuracy and sensitivity of the approach is estimated to be 86.7% and 83.3%, respectively, showing a good performance to be used as a decision support system.

Place, publisher, year, edition, pages
IOS Press, 2017. Vol. 238, p. 108-111
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 238
Keywords [en]
Time growing neural network; intelligent phonocardiography; machine learning; paediatric heart disease
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-145054PubMedID: 28679899ISBN: 978-1-61499-780-1 (print)ISBN: 978-1-61499-781-8 (electronic)OAI: oai:DiVA.org:liu-145054DiVA, id: diva2:1184195
Conference
nternational Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2017), Athens, Greece, July 2017
Available from: 2018-02-20 Created: 2018-02-20 Last updated: 2018-02-20

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PubMedhttp://10.3233/978-1-61499-781-8-108

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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