Deep Learning in Smart eHealth Systems [electronic resource] : Evaluation Leveraging for Parkinson's Disease / by Asma Channa, Nirvana Popescu.

Por: Channa, Asma [author.]Colaborador(es): Popescu, Nirvana [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries SpringerBriefs in Computer ScienceEditor: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XIII, 94 p. 35 illus., 33 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031450037Tema(s): 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 GraphicsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.31 Clasificación LoC:Q325.5-.7Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer Nature eBookResumen: 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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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.

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