Institution of Engineering and Technology

This edited book focuses on the applications of machine learning in the healthcare sector, both at the macro-level for guiding policy decisions, and at the granular level, showing how machine learning techniques can be applied to help individual patients.

This edited book discusses the challenges in handling medical data to provide effective healthcare services in real-time and outlines the approaches and the impact of, AI, IOT, cloud, big data, and blockchain technologies for building intelligent Healthcare 4.0 systems.

This edited book explores the use of mobile technologies such as phones, drones, robots, Apps, and wearable monitoring devices for improving access to healthcare for socially disadvantaged populations in remote, rural or developing regions.

This edited book focuses on the hardware systems for gait analysis such as speed, pressure, or body angles as well as data visualisation and mathematical models for interpreting this data. The book is written by a range of international researchers from academia, industry, and clinical settings.

This book examines machine learning trends in predictive technology to solve real-time healthcare problems. By using real-time data inputs to build predictive models, this new technology can model disease progression, assist with interventions or predict patient outcomes.

This edited book examines the application of blockchain technology and machine learning algorithms in various healthcare settings. This book covers the basic concepts of Blockchain and Machine Learning, and explores these issues with an eye on improving clinical outcomes and improving the patient's experience.

This book concentrates on sensing and measurement technologies for rehabilitation applications. The book looks at motion sensing technologies, human motion and exogames and healthcare applications including speech, respiration, and recovery from stroke or accident.

This book discusses the applications of distributed ledger technology in healthcare environments such as e-healthcare records and data security, health insurance management and fraud detection, pharmaceutical supply chain management and drug traceability, and IoT enabled patient monitoring.

This edited book discusses the technical considerations, potential opportunities and critical challenges of AI and blockchain in telehealth systems and presents case studies and critical lessons to consider when designing future AI and blockchain-based telehealth systems which have privacy and security in mind.

This edited book gives insights into the deployment, application, management, and benefits of explainable artificial intelligence (XAI) in medical decision support systems (MDSS). The book discusses XAI-based analytics for patient-specific MDSS as well as related security and privacy issues.

Addressing the physical layer security challenges and proposing efficient and resilient physical layer security solutions for beyond 5G networks leading to 6G, this book will help readers better understand the expectations of 6G's physical layer security in supporting a range of communications and sensing technologies.