Full Description
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.
Contents
Chapter 1: COVID-19 pandemic analysis using application of AI
Chapter 2: M-health: a revolution due to technology in healthcare sector
Chapter 3: Analysis of Big Data in electroencephalography (EEG)
Chapter 4: An analytical study of COVID-19 outbreak
Chapter 5: IoT-based smart healthcare monitoring system
Chapter 6: Development of a secured IoMT device with prioritized medical information for tracking and monitoring COVID patients in rural areas
Chapter 7: An IoT-based system for a volumetric estimation of human brain morphological features from magnetic resonance images
Chapter 8: Healthcare monitoring through IoT: security challenges and privacy issues
Chapter 9: E-health natural language processing
Chapter 10: Blockchain of things for healthcare asset management
Chapter 11: Artificial intelligence: practical primer for clinical research in cardiovascular disease
Chapter 12: Deep data analysis for COVID-19 outbreak
Chapter 13: Healthcare system using deep learning
Chapter 14: Intelligent classification of ECG signals using machine learning techniques
Chapter 15: A survey and taxonomy on mutual interference mitigation techniques in wireless body area networks
Chapter 16: Predicting COVID cases using machine learning, android, and firebase cloud storage
Chapter 17: Technological advancement with artificial intelligence in healthcare
Chapter 18: Changing dynamics on the Internet of Medical Things: challenges and opportunities
Chapter 19: Internet of Drones (IOD) in medical transport application
Chapter 20: Blockchain-based Internet of Things (IoT) for healthcare systems: COVID-19 perspective
Chapter 21: Artificial intelligence-based diseases detection and diagnosis in healthcare
