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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by CRC Press, 2025

    1032745169 / 9781032745169

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

  • Language: English

    Published by Auerbach Publications, 2025

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  • Language: English

    Published by CRC Press, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Auerbach Publications -, 2025

    1032745169 / 9781032745169

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    paperback. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032745169 / 9781032745169

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    Paperback. Condition: 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.…

  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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    Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Taylor & Francis Ltd, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

    • Softcover

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

    • Softcover

    Seller: California Books, Miami, FL, U.S.A.California Books

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  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032745169 / 9781032745169

    • Softcover

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    Paperback. Condition: 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.…

  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

    • Softcover

    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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  • Language: English

    Published by Auerbach Publications, 2025

    1032745169 / 9781032745169

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    Seller: Speedyhen, Hertfordshire, United KingdomSpeedyhen

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  • Language: English

    Published by CRC Press, 2025

    1032745169 / 9781032745169

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    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dr. K. Murugeswari is a Senior Assistant Professor in the School of Computing Science and Engineering at VIT Bhopal University, M.P, India.Dr. B. Sundaravadivazhagan is a professor in the Department of Information.

  • Language: English

    Published by Taylor & Francis Ltd, 2025

    1032745169 / 9781032745169

    • Softcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Paperback. Condition: Brand New. 308 pages. 9.18x6.12x9.21 inches. In Stock.

  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032745169 / 9781032745169

    • Softcover

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    Paperback. Condition: 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.…

  • Language: English

    Published by Taylor & Francis Ltd, London, 2025

    1032745169 / 9781032745169

    • Softcover

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    Paperback. Condition: new. Paperback. 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 patients 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. The book is a baseline reference for researchers and academicians who are investigating the application of deep learning algorithms in the healthcare sector. It focuses on medical imaging and healthcare data analytics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    1032745169 / 9781032745169

    • Softcover

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    Paperback. Condition: 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.…

  • Language: English

    Published by Auerbach Publications, 2024

    1032455810 / 9781032455815

    • Hardcover

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  • Language: English

    Published by Auerbach Publications 2024-05-15, 2024

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    Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Language: English

    Published by Auerbach Publications, 2024

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  • Language: English

    Published by Auerbach Publications, 2024

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  • Language: English

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  • Language: English

    Published by Auerbach Publications, 2024

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  • Language: English

    Published by Auerbach Publications, 2024

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  • Language: English

    Published by Auerbach Publications, 2024

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