Description

DEEP LEARNING FOR TREATMENTS

The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc.

Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare.

Audience
The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

Deep Learning for Targeted Treatments: Transformation in Healthcare

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£170.00

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Usually despatched within 5 days
Hardback by Rishabha Malviya , Gheorghita Ghinea

1 in stock

Short Description:

DEEP LEARNING FOR TREATMENTS The book provides the direction for future research in deep learning in terms of its role... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 28/09/2022
    ISBN13: 9781119857327, 978-1119857327
    ISBN10: 1119857325

    Number of Pages: 464

    Non Fiction , Computing

    Description

    DEEP LEARNING FOR TREATMENTS

    The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc.

    Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare.

    Audience
    The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

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