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020 _a9783031450037
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024 7 _a10.1007/978-3-031-45003-7
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100 1 _aChanna, Asma.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_993619
245 1 0 _aDeep Learning in Smart eHealth Systems
_h[electronic resource] :
_bEvaluation Leveraging for Parkinson's Disease /
_cby Asma Channa, Nirvana Popescu.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIII, 94 p. 35 illus., 33 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
505 0 _aUnraveling 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 _aOne 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.
650 0 _aMachine learning.
_91831
650 0 _aMedical informatics.
_94729
650 0 _aCloud Computing.
_94659
650 0 _aComputer science.
_99832
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_993622
650 1 4 _aMachine Learning.
_91831
650 2 4 _aHealth Informatics.
_931799
650 2 4 _aCloud Computing.
_94659
650 2 4 _aTheory and Algorithms for Application Domains.
_979177
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
700 1 _aPopescu, Nirvana.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_993624
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aSpringerBriefs in Computer Science,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-45003-7
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