Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Majestic Books, Hounslow, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 73,23
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Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 60,99
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 71,04
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 222 pages. 9.18x6.12x9.21 inches. In Stock.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: CitiRetail, Stevenage, Reino Unido
EUR 56,09
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Añadir al carritoPaperback. Condición: new. Paperback. Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors. This book will provide in depth information about handling and managing healthcare data by Machine Learning methods. It will express the long-standing challenges in healthcare informatics and provide rational orientations on how to deal with them. 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: moluna, Greven, Alemania
EUR 52,47
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Rashmi Agrawal is a Professor in the Department ofComputer Applications in MRIIRS, Faridabad. Dr.Agrawal has a rich teaching experience of more than 17years. She is UGC-NET(CS) qualified, and has completeda PhD, M. Phil, M. Te.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 89,30
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book will provide in depth information about handling and managing healthcare data by Machine Learning methods. It will express the long-standing challenges in healthcare informatics and provide rational orientations on how to deal with them.