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A Hybrid Model for Diagnosing Sever Aortic Stenosis in Asymptomatic Patients using Phonocardiogram
Malardalen University, Sweden.
Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Karolinska Institute, Sweden; Karolinska University Hospital, Sweden; KTH Royal Institute Technology, Sweden.
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2015 (English)In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, 2015, VOLS 1 AND 2, Springer, 2015, Vol. 51, 1006-1009 p.Conference paper (Refereed)
Abstract [en]

This study presents a screening algorithm for severe aortic stenosis (AS), based on a processing method for phonocardiographic (PCG) signal. The processing method employs a hybrid model, constituted of a hidden Markov model and support vector machine. The method benefits from a preprocessing phase for an enhanced learning. The performance of the method is statistically evaluated using PCG signals recorded from 50 individuals who were referred to the echocardiography lab at Linkoping University hospital. All the individuals were diagnosed as having a degree of AS, from mild to severe, according to the echocardiographic measurements. The patient group consists of 26 individuals with severe AS, and the rest of the 24 patients comprise the control group. Performance of the method is statistically evaluated using repeated random sub sampling. Results showed a 95% confidence interval of (80.5%-82.8%)/(77.8%-80.8%) for the accuracy/sensitivity, exhibiting an acceptable performance to be used as decision support system in the primary healthcare center.

Place, publisher, year, edition, pages
Springer, 2015. Vol. 51, 1006-1009 p.
, IFMBE Proceedings, ISSN 1680-0737
Keyword [en]
Aortic stenosis; phonocardiogram; hybrid model; decision support; primary healthcare centers
National Category
Biomedical Laboratory Science/Technology
URN: urn:nbn:se:liu:diva-131738DOI: 10.1007/978-3-319-19387-8_245ISI: 000381813000245ISBN: 978-3-319-19387-8ISBN: 978-3-319-19386-1OAI: diva2:1002467
World Congress on Medical Physics and Biomedical Engineering
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2016-09-30

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Ask, PerNylander, EvaEkman, IngerBabic, Ankica
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Physiological MeasurementsFaculty of Science & EngineeringDivision of Cardiovascular MedicineFaculty of Medicine and Health SciencesDepartment of Clinical Physiology in LinköpingCenter for Medical Image Science and Visualization (CMIV)Medical Informatics
Biomedical Laboratory Science/Technology

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