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Deep Learning in Smart eHealth Systems

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Deep Learning in Smart eHealth Systems Synopsis

One of the main benefits of this book is that it presents a comprehensive and innovative eHealth framework that leverages deep learning and IoT wearable devices for the evaluation of Parkinson's disease patients. This framework offers a new way to assess and monitor patients' motor deficits in a personalized and automated way, improving the efficiency and accuracy of diagnosis and treatment.

Compared to other books on eHealth and Parkinson's disease, this book offers a unique perspective and solution to the challenges facing patients and healthcare providers. It combines state-of-the-art technology, such as wearable devices and deep learning algorithms, with clinical expertise to develop a personalized and efficient evaluation framework for Parkinson's disease patients.

This book provides a roadmap for the integration of cutting-edge technology into clinical practice, paving the way for more effective and patient-centered healthcare. To understand this book, readers should have a basic knowledge of eHealth, IoT, deep learning, and Parkinson's disease. However, the book provides clear explanations and examples to make the content accessible to a wider audience, including researchers, practitioners, and students interested in the intersection of technology and healthcare.

About This Edition

ISBN: 9783031450020
Publication date:
Author: Asma Channa, Nirvana Popescu
Publisher: Springer an imprint of Springer Nature Switzerland
Format: Paperback
Pagination: 94 pages
Series: SpringerBriefs in Computer Science
Genres: Machine learning
Image processing
Cloud computing
Computer applications in industry and technology
Mathematical theory of computation

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