Deep Learning and IoT in Healthcare Systems
Paradigms and Applications
1st Edition
Published on 14. December 2021
348 pages
978-1-000-08918-9 (ISBN)
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 in conjunction with IoT used by practitioners and researchers worldwide.
The authors explore 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 also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
The authors explore 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 also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
Illustrations
23 Tables, black and white; 8 Line drawings, color; 69 Line drawings, black and white; 6 Halftones, black and white; 8 Illustrations, color; 75 Illustrations, black and white
ISBN-13
978-1-000-08918-9 (9781000089189)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Krishna Kant Singh | Akansha Singh | Jenn-Wei Lin
Deep Learning and IoT in Healthcare Systems
Paradigms and Applications
Book
07/2024
1st Edition
Apple Academic Press Inc.
€132.50
Shipment within 3-4 weeks
Krishna Kant Singh | Akansha Singh | Jenn-Wei Lin
Deep Learning and IoT in Healthcare Systems
Paradigms and Applications
Book
12/2021
1st Edition
Apple Academic Press Inc.
€230.60
Shipment within 3-4 weeks
Persons
Krishna Kant Singh, PhD, is Professor in Computer Science and Engineering, Faculty of Engineering and Technology, Jain (Deemed-to-be University), Bengaluru, India. He has wide teaching and research experience. He has authored more than 50 research papers in Scopus- and SCIE-indexed journals as well as 25 technical books. He is also Associate Editor of the Journal of Intelligent & Fuzzy Systems and IEEE ACCESS and a guest editor of Open Computer Science. He is also a member of the editorial board for Applied Computing & Geoscience.
Akansha Singh, PhD, is Associate Professor in the Department of Computer Science and Engineering, ASET, Amity University, Noida, India. She has to her credit more than 40 research papers, 20 books, and numerous conference papers. She has been the editor for books on emerging topics and has served as a reviewer and technical committee member for multiple conferences and journals. She is also the Associate Editor for IEEE Access. Dr. Singh has also undertaken a government-funded project as a principal investigator. Her research areas include image processing, remote sensing, IoT, and machine learning.
Jenn-Wei Lin, PhD, is Professor with the Department of Computer Science and Information Engineering, Fu Jen Catholic University, Taiwan. Prior to that, he was a researcher with Chunghwa Telecom Co., Ltd., Taoyuan, Taiwan, from 1993 to 2001. His current research interests include cloud computing, mobile computing and networks, distributed systems, and fault-tolerant computing.
Ahmed A. Elngar, PhD, is the Founder and Head of Scientific Innovation Research Group and Assistant Professor in the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt, where he is also Director of the Technological and Informatics Studies Center. Dr. Elngar has published more than 25 scientific research papers and several books. He participates in many professional activities such as organizing workshops hosted by universities throughout Egypt.
Akansha Singh, PhD, is Associate Professor in the Department of Computer Science and Engineering, ASET, Amity University, Noida, India. She has to her credit more than 40 research papers, 20 books, and numerous conference papers. She has been the editor for books on emerging topics and has served as a reviewer and technical committee member for multiple conferences and journals. She is also the Associate Editor for IEEE Access. Dr. Singh has also undertaken a government-funded project as a principal investigator. Her research areas include image processing, remote sensing, IoT, and machine learning.
Jenn-Wei Lin, PhD, is Professor with the Department of Computer Science and Information Engineering, Fu Jen Catholic University, Taiwan. Prior to that, he was a researcher with Chunghwa Telecom Co., Ltd., Taoyuan, Taiwan, from 1993 to 2001. His current research interests include cloud computing, mobile computing and networks, distributed systems, and fault-tolerant computing.
Ahmed A. Elngar, PhD, is the Founder and Head of Scientific Innovation Research Group and Assistant Professor in the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef, Egypt, where he is also Director of the Technological and Informatics Studies Center. Dr. Elngar has published more than 25 scientific research papers and several books. He participates in many professional activities such as organizing workshops hosted by universities throughout Egypt.
Content
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 in 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 Systems 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)
