Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 61,24
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 67,60
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Condizione: New. pages cm First edition Includes bibliographical references and index.
EUR 75,76
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 62,71
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 62,55
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 62,56
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
EUR 71,07
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EUR 73,08
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 69,91
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Da: Majestic Books, Hounslow, Regno Unito
EUR 81,07
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
EUR 90,56
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Da: Chiron Media, Wallingford, Regno Unito
EUR 77,09
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Aggiungi al carrellopaperback. Condizione: New.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032745169 ISBN 13: 9781032745169
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 79,54
Quantità: 1 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 80,08
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 89,94
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032745169 ISBN 13: 9781032745169
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 103,00
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.
Da: Revaluation Books, Exeter, Regno Unito
EUR 90,66
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 276 pages. 10.00x7.00x10.00 inches. In Stock.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 94,73
Quantità: 3 disponibili
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EUR 69,92
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Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 128,38
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Da: Revaluation Books, Exeter, Regno Unito
EUR 118,01
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Aggiungi al carrelloPaperback. Condizione: Brand New. 308 pages. 9.18x6.12x9.21 inches. In Stock.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2025
ISBN 10: 1032745169 ISBN 13: 9781032745169
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
Paperback. Condizione: New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.