Extended Reality for Healthcare Systems: Recent Advances in Contemporary Research focuses on real world applications in medicine, also providing an overview of emerging technologies. The book includes case studies that break down the ways in which this technology has and can be used, while also taking readers through evidence, best practices and obstacles. Sections emphasize evidence, research-based practices and work. Content coverage includes Enhancing Medical Education with AR/VR, and XR: The Future of Surgery and Building Systems for Enhanced Health, and more. Readers will learn how to use this technology to improve existing systems by enhancing precision and reducing costs. Other sections cover extended reality in elderly care and remote monitoring of patients, building systems for enhanced health, including telehealth and telepsychiatry, using AR and VR in medical education, and designing technology for use in telesurgery.

This book focuses on data analytics with machine learning using IoT and blockchain technology. Integrating these three fields by examining their interconnections, Intelligent Data Analytics, IoT, and Blockchain examines the opportunities and challenges of developing systems and applications exploiting these technologies. Written primarily for researchers who are working in this multi-disciplinary field, the book also benefits industry experts and technology executives who want to develop their organizations' decision-making capabilities. Highlights of the book include: Using image processing with machine learning techniques A deep learning approach for facial recognition A scalable system architecture for smart cities based on cognitive IoT Source authentication of videos shared on social media Survey of blockchain in healthcare Accident prediction by vehicle tracking Big Data analytics in disaster management An exploration of blockchain technology from the perspective of applicability, limitations, and opportunities The book presents novel ideas and insights on different aspects of data analytics, blockchain technology, and IoT. It views these technologies as interdisciplinary fields about processes and systems that extract knowledge and insights from data. Focusing on recent advancements, the book offers a variety of solutions to real-life challenges with an emphasis on security.

AI-Based Data Analytics: Applications for Business Management covers various topics related to marketing and business analytics. It explores how organizations can increase their profits by making better decisions in a timely manner through the use of data analytics. This book is meant for students, practitioners, industry professionals, researchers, and academics working in the field of commerce and marketing, big data analytics, and organizational decision-making. Highlights of the book include: The role of Explainable AI in improving customer experiences in e-commerce Sentiment analysis of social media Data analytics in business intelligence Federated learning for business intelligence AI-based planning of business management An AI-based business model innovation in new technologies An analysis of social media marketing and online impulse buying behaviour The book has two primary focuses. The first is on analytics for decision-making and covers big data analytics for market intelligence, data analytics and consumer behavior, and the role of big data analytics in organizational decision-making. The book’s second focus is on digital marketing and includes the prediction of marketing by consumer analytics, web analytics for digital marketing, smart retailing, and leveraging web analytics for optimizing digital marketing strategies.

Presents concepts of data for business decision making as well as algorithms and models used to analyze data used to solve business problems. Use data analytics to inform decisions related to product price and possession utilities Market products on the basis of consumer analytics

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.

1. Addresses a broad range of cyber security issues of modern networks 2. The book will comprise state-of-the-art techniques, methods and solutions for today's privacy / security issues. 3. Interdisciplinary approaches for countering the latest attacks on networks. 4. Will be excellent book for students, postgraduates and professionals.

Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics.