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ISBN 10: 1032487372 ISBN 13: 9781032487373
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ISBN 10: 1032487372 ISBN 13: 9781032487373
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health recordsFocuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systemsShowcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare servicesDiscusses unsupervised genetic algorithm-based automatic heart disease predictionCovers Internet of Things-based hardware mechanisms and machine learning algorithms to predict the stress level of patientsThe text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology. 226 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr Prasenjit Dey received his B.Tech. degree in computer science and engineering from the West Bengal University of Technology, Kolkata, India, in 2010, and the M.Tech. degree in computer science and engineering from the National Institute of Tech.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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Hardcover. Condition: new. Hardcover. The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health recordsFocuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systemsShowcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare servicesDiscusses unsupervised genetic algorithm-based automatic heart disease predictionCovers Internet of Thingsbased hardware mechanisms and machine learning algorithms to predict the stress level of patientsThe text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology. Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., accelerometer, electrocardiography, and electroencephalography. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Chapman And Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health recordsFocuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systemsShowcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare servicesDiscusses unsupervised genetic algorithm-based automatic heart disease predictionCovers Internet of Things-based hardware mechanisms and machine learning algorithms to predict the stress level of patientsThe text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032487372 ISBN 13: 9781032487373
Language: English
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Internet of Things-Based Machine Learning in Healthcare | Technology and Applications | Prasenjit Dey (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9781032487373 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.