Saqib Hakak – författare

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.

Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting user social behavior (known as sentiment analysis for healthcare-related purposes) round out the diverse array of topics this reference book covers.

Contributions from experts in the field, this book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.

Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting user social behavior (known as sentiment analysis for healthcare-related purposes) round out the diverse array of topics this reference book covers.

Contributions from experts in the field, this book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

The Internet of Things (IoT) concept has emerged partly due to information and communication technology developments and societal needs, expanding the ability to connect numerous objects. The wide range of facilities enabled by IoT has generated a vast amount of data, making cybersecurity an imperative requirement for personal safety and for ensuring the sustainability of the IoT ecosystem. This book covers security and privacy research in the IoT domain, compiling technical and management approaches, addressing real-world problems, and providing practical advice to the industry. This book also includes a collection of research works covering key emerging trends in IoT security and privacy that span the entire IoT architecture layers, focusing on different critical IoT applications such as advanced metering infrastructure and smart grids, smart locks, and cyber-physical systems.

The provided state-of-the-art body of knowledge is essential for researchers, practitioners, postgraduate students, and developers interested in the security and privacy of the IoT paradigm, IoT-based systems, and any related research discipline. This book is a valuable companion and comprehensive reference for postgraduate and senior undergraduate students taking an advanced IoT security and privacy course.

The Internet of Things (IoT) concept has emerged partly due to information and communication technology developments and societal needs, expanding the ability to connect numerous objects. The wide range of facilities enabled by IoT has generated a vast amount of data, making cybersecurity an imperative requirement for personal safety and for ensuring the sustainability of the IoT ecosystem. This book covers security and privacy research in the IoT domain, compiling technical and management approaches, addressing real-world problems, and providing practical advice to the industry. This book also includes a collection of research works covering key emerging trends in IoT security and privacy that span the entire IoT architecture layers, focusing on different critical IoT applications such as advanced metering infrastructure and smart grids, smart locks, and cyber-physical systems.

The provided state-of-the-art body of knowledge is essential for researchers, practitioners, postgraduate students, and developers interested in the security and privacy of the IoT paradigm, IoT-based systems, and any related research discipline. This book is a valuable companion and comprehensive reference for postgraduate and senior undergraduate students taking an advanced IoT security and privacy course.