IoT-enabled healthcare technologies can be used for remote health monitoring, rehabilitation assessment and assisted ambient living. Healthcare analytics can be applied to the data gathered from these different areas to improve healthcare outcomes by providing clinicians with real-world, real-time data so they can more easily support and advise their patients. The book explores the application of AI systems to analyse patient data and guide interventions. IoT-based monitoring systems and their security challenges are also discussed. The book is designed to be a reference for healthcare informatics researchers, developers, practitioners, and people who are interested in the personalised healthcare sector. The book will be a valuable reference tool for those who identify and develop methodologies, frameworks, tools, and applications for working with medical big data and researchers in computer engineering, healthcare electronics, device design and related fields.
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This edited book covers big data analysis methods of patient data gained via IoT-enabled monitoring systems. The information gathered can be processed to aid clinicians with diagnoses, prognoses and interventions. This book is a great reference to those using, designing, modelling and analysing intelligent healthcare services.
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Chapter 1: COVID-19 pandemic analysis using application of AIChapter 2: M-health: a revolution due to technology in healthcare sectorChapter 3: Analysis of Big Data in electroencephalography (EEG)Chapter 4: An analytical study of COVID-19 outbreakChapter 5: IoT-based smart healthcare monitoring systemChapter 6: Development of a secured IoMT device with prioritized medical information for tracking and monitoring COVID patients in rural areasChapter 7: An IoT-based system for a volumetric estimation of human brain morphological features from magnetic resonance imagesChapter 8: Healthcare monitoring through IoT: security challenges and privacy issuesChapter 9: E-health natural language processingChapter 10: Blockchain of things for healthcare asset managementChapter 11: Artificial intelligence: practical primer for clinical research in cardiovascular diseaseChapter 12: Deep data analysis for COVID-19 outbreakChapter 13: Healthcare system using deep learningChapter 14: Intelligent classification of ECG signals using machine learning techniquesChapter 15: A survey and taxonomy on mutual interference mitigation techniques in wireless body area networksChapter 16: Predicting COVID cases using machine learning, android, and firebase cloud storageChapter 17: Technological advancement with artificial intelligence in healthcareChapter 18: Changing dynamics on the Internet of Medical Things: challenges and opportunitiesChapter 19: Internet of Drones (IOD) in medical transport applicationChapter 20: Blockchain-based Internet of Things (IoT) for healthcare systems: COVID-19 perspectiveChapter 21: Artificial intelligence-based diseases detection and diagnosis in healthcare
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Produktdetaljer

ISBN
9781839534379
Publisert
2022-04-20
Utgiver
Vendor
Institution of Engineering and Technology
Høyde
234 mm
Bredde
156 mm
Aldersnivå
U, P, 05, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
424

Biographical note

Vishal Jain is an associate professor at the Department of Computer Science and Engineering, Sharda University, India. He was awarded Young Active Member Award (2012-13) from the Computer Society of India, Best Faculty Award (2017), and Best Researcher Award (2019) from BVICAM, New Delhi. He has published over 70 peer-reviewed papers and 10 books. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks. Jyotir Moy Chatterjee is an assistant professor in the Information Technology Department at Lord Buddha Education Foundation (LBEF), Nepal. He has been a member of the organizing committee of various international conferences (IEEE, Springer, Elsevier) and serves as a reviewer for numerous international journals. His research interests include the Internet of Things, machine learning, and deep learning. He has published 22 research papers, 3 international conference papers, 28 books, and 16 chapters. Pardeep Kumar is a professor and the head of the Software Engineering Department, QUEST University, Nawabshah, Pakistan. He is also the director for the Office of Research, Innovation and Commercialization (ORIC). His research interests include wireless communication, wireless sensor networks, distributed and embedded systems and IoT technologies. Dr. Kumar has been an author/editor of 4 books, several book chapters, and more than 50 research publications. Utku Kose is an associate professor at the Department of Computer Engineering of Süleyman Demirel University, Turkey. He has published more than 200 journal papers, conference presentations, keynote speeches and book chapters. His research interests include artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos theory, distance education, e-learning, computer education, and computer science.