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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.
Autorius: | Nirvana Popescu, Asma Channa, |
Serija: | SpringerBriefs in Computer Science |
Leidėjas: | Springer Nature Switzerland |
Išleidimo metai: | 2023 |
Knygos puslapių skaičius: | 108 |
ISBN-10: | 3031450027 |
ISBN-13: | 9783031450020 |
Formatas: | 235 x 155 x 6 mm. Knyga minkštu viršeliu |
Kalba: | Anglų |
Parašykite atsiliepimą apie „Deep Learning in Smart eHealth Systems: Evaluation Leveraging for Parkinson¿s Disease“