Channa, Asma.
Deep Learning in Smart eHealth Systems Evaluation Leveraging for Parkinson's Disease / [electronic resource] : by Asma Channa, Nirvana Popescu. - 1st ed. 2024. - XIII, 94 p. 35 illus., 33 illus. in color. online resource. - 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.
9783031450037
10.1007/978-3-031-45003-7 doi
Machine learning.
Medical informatics.
Cloud Computing.
Computer science.
Image processing--Digital techniques.
Computer vision.
Machine Learning.
Health Informatics.
Cloud Computing.
Theory and Algorithms for Application Domains.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Q325.5-.7
006.31
Deep Learning in Smart eHealth Systems Evaluation Leveraging for Parkinson's Disease / [electronic resource] : by Asma Channa, Nirvana Popescu. - 1st ed. 2024. - XIII, 94 p. 35 illus., 33 illus. in color. online resource. - 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.
9783031450037
10.1007/978-3-031-45003-7 doi
Machine learning.
Medical informatics.
Cloud Computing.
Computer science.
Image processing--Digital techniques.
Computer vision.
Machine Learning.
Health Informatics.
Cloud Computing.
Theory and Algorithms for Application Domains.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Q325.5-.7
006.31