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.
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.
- 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