The phonocardiogram (PCG) is a non-invasive bio-sound signal used to identify cardiovascular pathologies and assess their severity. This work follows studies that have demonstrated the value of Higher-Order Spectral Analysis (HOSA) techniques for monitoring cardiac severity. HOSA features were extracted and then selected using Random Forest Feature Importance and SelectKBest methods. They were subsequently integrated into a k-Nearest Neighbor (KNN) classifier. Out of fourteen initial features, four achieved an accuracy of 99.7%, confirming the relevance of this approach for PCG signal analysis.
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Autorka posiada stopie¿ doktora w zakresie aparatury biomedycznej. Jej prace dotycz¿ in¿ynierii, analizy sygnäów oraz ich zastosowä biomedycznych. Angäuje si¿ równie¿ w opiek¿ pedagogiczn¿ oraz upowszechnianie wiedzy naukowej poprzez publikacje i projekty.
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Paperback. Zustand: new. Paperback. The phonocardiogram (PCG) is a non-invasive bio-sound signal used to identify cardiovascular pathologies and assess their severity. This work follows studies that have demonstrated the value of Higher-Order Spectral Analysis (HOSA) techniques for monitoring cardiac severity. HOSA features were extracted and then selected using Random Forest Feature Importance and SelectKBest methods. They were subsequently integrated into a k-Nearest Neighbor (KNN) classifier. Out of fourteen initial features, four achieved an accuracy of 99.7%, confirming the relevance of this approach for PCG signal analysis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786209453632
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The phonocardiogram (PCG) is a non-invasive bio-sound signal used to identify cardiovascular pathologies and assess their severity. This work follows studies that have demonstrated the value of Higher-Order Spectral Analysis (HOSA) techniques for monitoring cardiac severity. HOSA features were extracted and then selected using Random Forest Feature Importance and SelectKBest methods. They were subsequently integrated into a k-Nearest Neighbor (KNN) classifier. Out of fourteen initial features, four achieved an accuracy of 99.7%, confirming the relevance of this approach for PCG signal analysis. Bestandsnummer des Verkäufers 9786209453632
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Paperback. Zustand: new. Paperback. The phonocardiogram (PCG) is a non-invasive bio-sound signal used to identify cardiovascular pathologies and assess their severity. This work follows studies that have demonstrated the value of Higher-Order Spectral Analysis (HOSA) techniques for monitoring cardiac severity. HOSA features were extracted and then selected using Random Forest Feature Importance and SelectKBest methods. They were subsequently integrated into a k-Nearest Neighbor (KNN) classifier. Out of fourteen initial features, four achieved an accuracy of 99.7%, confirming the relevance of this approach for PCG signal analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209453632
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