Isbn: 9789999345811 - intelligent acoustic cardiology: multi-fractal signal processing and machine learning for early valvular disease detection (8 resultados)

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  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999345816 / 9789999345811

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Editorial: Eliva Press, 2026

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Condición: Nuevo

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    Paperback. Condición: Brand New. 102 pages. 6.00x0.23x9.00 inches. In Stock.

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999345816 / 9789999345811

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    Paperback. Condición: new. Paperback. This book has systematically explored the intersection of advanced signal processing techniques and artificial intelligence (AI) methodologies in the early detection and management of cardiac pathologies. As cardiovascular diseases (CVDs) continue to be a leading global health challenge, the need for innovative, non-invasive diagnostic methods is more pressing than ever. The research has demonstrated that enhancing the analysis of phonocardiogram (PCG) signals through advanced signal processing not only improves the signal-to-noise ratio but also clarifies cardiac sounds, facilitating more accurate interpretations. By developing tailored machine learning algorithms, this work significantly contributes to the automation of pathological feature detection in PCG signals, paving the way for timely and precise diagnoses. The integration of AI with conventional cardiac monitoring practices has been shown to enhance diagnostic accuracy and positively influence clinical outcomes. By proposing a comprehensive framework that incorporates these advanced techniques, this book lays the groundwork for a transformative approach to cardiac disease management, emphasizing the importance of timely clinical interventions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999345816 / 9789999345811

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Paperback. Condición: new. Paperback. This book has systematically explored the intersection of advanced signal processing techniques and artificial intelligence (AI) methodologies in the early detection and management of cardiac pathologies. As cardiovascular diseases (CVDs) continue to be a leading global health challenge, the need for innovative, non-invasive diagnostic methods is more pressing than ever. The research has demonstrated that enhancing the analysis of phonocardiogram (PCG) signals through advanced signal processing not only improves the signal-to-noise ratio but also clarifies cardiac sounds, facilitating more accurate interpretations. By developing tailored machine learning algorithms, this work significantly contributes to the automation of pathological feature detection in PCG signals, paving the way for timely and precise diagnoses. The integration of AI with conventional cardiac monitoring practices has been shown to enhance diagnostic accuracy and positively influence clinical outcomes. By proposing a comprehensive framework that incorporates these advanced techniques, this book lays the groundwork for a transformative approach to cardiac disease management, emphasizing the importance of timely clinical interventions. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999345816 / 9789999345811

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Paperback. Condición: new. Paperback. This book has systematically explored the intersection of advanced signal processing techniques and artificial intelligence (AI) methodologies in the early detection and management of cardiac pathologies. As cardiovascular diseases (CVDs) continue to be a leading global health challenge, the need for innovative, non-invasive diagnostic methods is more pressing than ever. The research has demonstrated that enhancing the analysis of phonocardiogram (PCG) signals through advanced signal processing not only improves the signal-to-noise ratio but also clarifies cardiac sounds, facilitating more accurate interpretations. By developing tailored machine learning algorithms, this work significantly contributes to the automation of pathological feature detection in PCG signals, paving the way for timely and precise diagnoses. The integration of AI with conventional cardiac monitoring practices has been shown to enhance diagnostic accuracy and positively influence clinical outcomes. By proposing a comprehensive framework that incorporates these advanced techniques, this book lays the groundwork for a transformative approach to cardiac disease management, emphasizing the importance of timely clinical interventions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999345816 / 9789999345811

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    EUR 55,55

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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Intelligent Acoustic Cardiology | Multi-Fractal Signal Processing and Machine Learning for Early Valvular Disease Detection | Hakkoum Khaoula Nour El Houda (u. a.) | Taschenbuch | Englisch | 2026 | Eliva Press | EAN 9789999345811 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …