Deep Learning and IoT in Healthcare Systems: Paradigms and Applications

Description

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. Cover Half Title Title Page Copyright Page About the Editors Table of Contents Contributors Abbreviations Preface 1. Deep Learning for Healthcare 2. Role of AI in Healthcare 3. Case Studies: Healthcare and Deep Learning 4. Assistive Devices and IoT in Healthcare Functions 5. Impact of IoT on Healthcare‑Assistive Devices 6. Smart Fall Detection Systems for Elderly Care 7. Smart Sensors Transform Healthcare System 8. Healthcare Applications of the Internet of Things (IoT) 9. Mobile‑App‑Enabled System for Healthcare 10. Energy-Efficient Network Design for Healthcare Services 11. Applying Data Mining to Detect the Mental State and Small Muscle Movements for Individuals with Autism Spectrum Disorder (ASD) Index