Deep Learning in Smart eHealth Systems : Evaluation Leveraging for Parkinson’s Disease / by Asma Channa, Nirvana Popescu.

Format:

Book

Author/Creator:

Channa, Asma.

Contributor:

Popescu, Nirvana.

Series:

SpringerBriefs in Computer Science, 2191-5776

Language:

English

Subjects (All):

Machine learning.

Medical informatics.

Cloud computing.

Computer science.

Image processing--Digital techniques.

Image processing.

Computer vision.

Machine Learning.

Health Informatics.

Cloud Computing.

Theory and Algorithms for Application Domains.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Machine Learning.

Health Informatics.

Cloud Computing.

Theory and Algorithms for Application Domains.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (102 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

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.

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Channa, Asma Deep Learning in Smart EHealth Systems

ISBN:

3-031-45003-5

OCLC:

1409032564