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Deep Learning and IoT in Healthcare Systems: Paradigms and Applications
This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It describes deep learning techniques along with IoT used by practitioners and researchers worldwide.
The authors look at the role and impact that deep learning and the IoT plays in healthcare systems, such as the convergence of IoT and deep learning to enable things to communicate, share information, and coordinate decisions. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology.
Chapters look at assistive devices in healthcare, alerting and detection devices, energy efficiency in using IoT, data mining for gathering health information for individuals with autism, IoT for mobile applications, and more.
The text offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
The authors look at the role and impact that deep learning and the IoT plays in healthcare systems, such as the convergence of IoT and deep learning to enable things to communicate, share information, and coordinate decisions. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology.
Chapters look at assistive devices in healthcare, alerting and detection devices, energy efficiency in using IoT, data mining for gathering health information for individuals with autism, IoT for mobile applications, and more.
The text offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
348 pages, Paperback
Published July 8, 2024
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