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A hybrid machine learning method for detecting cardiac ejection murmurs
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
CAPIS Biomedical Research and Department Center, Mons, Belgium.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
Linköping University, Sweden.
2017 (English)In: IFMBE Proceedings, Springer Verlag , 2017, 787-790 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel method for detecting cardiac ejection murmurs from other pathological and physiological heart murmurs in children. The proposed method combines a hybrid model and a time growing neural network for an improved detection even in mild condition. Children with aortic stenosis and pulmonary stenosis comprised the patient category against the reference category containing mitral regurgitation, ventricular septal defect, innocent murmur and normal (no murmur) conditions. In total, 120 referrals to a children University hospital participated to the study after giving their informed consent. Confidence interval of the accuracy, sensitivity and specificity is estimated to be 87.2% ̶ 88.8%, 83.4% ̶ 86.9% and 88.3% ̶ 90.0%, respectively. 

Place, publisher, year, edition, pages
Springer Verlag , 2017. 787-790 p.
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-36136DOI: 10.1007/978-981-10-5122-7_197Scopus ID: 2-s2.0-85021746804ISBN: 9789811051210 OAI: oai:DiVA.org:mdh-36136DiVA: diva2:1128721
Conference
Joint Conference of the European Medical and Biological Engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2107, 11 June 2017 through 15 June 2017
Available from: 2017-07-27 Created: 2017-07-27 Last updated: 2017-07-27Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
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  • fi-FI
  • nn-NO
  • nn-NB
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