Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 57,22
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 90,70
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Añadir al carritoPaperback. Condición: Brand New. 306 pages. 9.18x6.12x9.21 inches. In Stock.
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 57,97
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 76,52
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 73,34
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Añadir al carritoCondición: New. volumes cm First edition Includes bibliographical references and index.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 65,00
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 71,82
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Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 1032300787 ISBN 13: 9781032300788
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 59,57
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Añadir al carritoPaperback. Condición: new. Paperback. This book intends to present emerging Federated Learning (FL)-based architectures, frameworks, and models in Internet of Medical Things (IoMT) applications. It intends to build on the basics of the healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. Once IoMT is presented, the book shifts towards the proposal of privacy-preservation in IoMT, and explains how FL presents a viable solution to these challenges. The claims are supported through lucid illustrations, tables, and examples that present effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in a simple manner. The book intends to create opportunities for healthcare communities to build effective FL solutions around the presented themes, and to support work in related areas that will benefit from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in the IoMT domain. The emphasis of this book is on understanding the contributions of IoMT to healthcare analytics, and its aim is to provide insights including evolution, research directions, challenges, and the way to empower healthcare services through federated learning.The book also intends to cover the ethical and social issues around the recent advancements in the field of decentralized Artificial Intelligence. The book is mainly intended for undergraduates, post-graduates, researchers, and healthcare professionals who wish to learn FL-based solutions right from scratch, and build practical FL solutions in different IoMT verticals. The book intends to present emerging Federated Learning (FL) based architectures, frameworks, and models in Internet-of-Medical Things (IoMT) applications. It intends to build up onto the basics of healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 76,48
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 1032300787 ISBN 13: 9781032300788
Librería: CitiRetail, Stevenage, Reino Unido
EUR 57,98
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. This book intends to present emerging Federated Learning (FL)-based architectures, frameworks, and models in Internet of Medical Things (IoMT) applications. It intends to build on the basics of the healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. Once IoMT is presented, the book shifts towards the proposal of privacy-preservation in IoMT, and explains how FL presents a viable solution to these challenges. The claims are supported through lucid illustrations, tables, and examples that present effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in a simple manner. The book intends to create opportunities for healthcare communities to build effective FL solutions around the presented themes, and to support work in related areas that will benefit from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in the IoMT domain. The emphasis of this book is on understanding the contributions of IoMT to healthcare analytics, and its aim is to provide insights including evolution, research directions, challenges, and the way to empower healthcare services through federated learning.The book also intends to cover the ethical and social issues around the recent advancements in the field of decentralized Artificial Intelligence. The book is mainly intended for undergraduates, post-graduates, researchers, and healthcare professionals who wish to learn FL-based solutions right from scratch, and build practical FL solutions in different IoMT verticals. The book intends to present emerging Federated Learning (FL) based architectures, frameworks, and models in Internet-of-Medical Things (IoMT) applications. It intends to build up onto the basics of healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: preigu, Osnabrück, Alemania
EUR 77,95
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Federated Learning for Internet of Medical Things | Concepts, Paradigms, and Solutions | Pronaya Bhattacharya (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032300788 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 93,14
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book intends to present emerging Federated Learning (FL) based architectures, frameworks, and models in Internet-of-Medical Things (IoMT) applications. It intends to build up onto the basics of healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing.