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Deep learning in smart eHealth systems = evaluation leveraging for Parkinson's disease /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning in smart eHealth systems/ by Asma Channa, Nirvana Popescu.
Reminder of title:	evaluation leveraging for Parkinson's disease /
Author:	Channa, Asma.
other author:	Popescu, Nirvana.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xiii, 94 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Unraveling Parkinson's Disease: Diagnostic Challenges and Severity Assessment -- State-of-the-Art: Wearable Devices and Deep Learning Techniques for Parkinson's Disease -- Design and Engineering of a Medical Wearable Device for Parkinson's Disease Management -- Deep Learning Models for Parkinson's Disease Severity Evaluation -- Transforming Parkinson's Disease Care: Cloud Service Empowered by ServiceNow Technology -- Predicting Wearing-Off Episodes in Parkinson's with Multimodal Machine Learning -- Enhancing Gait Analysis Through Wearable Insoles and Deep Learning Techniques -- Conclusion and Prospects for Further Development.
Contained By:	Springer Nature eBook
Subject:	Parkinson's disease. -
Online resource:	https://doi.org/10.1007/978-3-031-45003-7
ISBN:	9783031450037

Deep learning in smart eHealth systems = evaluation leveraging for Parkinson's disease /
Channa, Asma.

Deep learning in smart eHealth systemsevaluation leveraging for Parkinson's disease /[electronic resource] :by Asma Channa, Nirvana Popescu. - Cham :Springer Nature Switzerland :2024. - xiii, 94 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..

Unraveling Parkinson's Disease: Diagnostic Challenges and Severity Assessment -- State-of-the-Art: Wearable Devices and Deep Learning Techniques for Parkinson's Disease -- Design and Engineering of a Medical Wearable Device for Parkinson's Disease Management -- Deep Learning Models for Parkinson's Disease Severity Evaluation -- Transforming Parkinson's Disease Care: Cloud Service Empowered by ServiceNow Technology -- Predicting Wearing-Off Episodes in Parkinson's with Multimodal Machine Learning -- Enhancing Gait Analysis Through Wearable Insoles and Deep Learning Techniques -- Conclusion and Prospects for Further Development.

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.

ISBN: 9783031450037

Standard No.: 10.1007/978-3-031-45003-7doiSubjects--Topical Terms:

844182
Parkinson's disease.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.28563

Deep learning in smart eHealth systems = evaluation leveraging for Parkinson's disease /
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505 0 $a Unraveling Parkinson's Disease: Diagnostic Challenges and Severity Assessment -- State-of-the-Art: Wearable Devices and Deep Learning Techniques for Parkinson's Disease -- Design and Engineering of a Medical Wearable Device for Parkinson's Disease Management -- Deep Learning Models for Parkinson's Disease Severity Evaluation -- Transforming Parkinson's Disease Care: Cloud Service Empowered by ServiceNow Technology -- Predicting Wearing-Off Episodes in Parkinson's with Multimodal Machine Learning -- Enhancing Gait Analysis Through Wearable Insoles and Deep Learning Techniques -- Conclusion and Prospects for Further Development.
520 $a 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.
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