The book provides comprehensive research ideas about Edge-AI technology that can assist doctors in making better data-driven decisions. It provides insights for improving the healthcare industry by examining future trends, simplifying decision making and investigating structured and unstructured data. Edge-AI in Healthcare: Trends and Future Perspective is more than a comprehensive introduction to Artificial Intelligence as a tool in healthcare data. The book is split into five chapters covering the entire healthcare ecosystem. First section is introduction to Edge-AI in healthcare. It discusses data usage, modelling and simulation techniques as well as machine and deep learning approaches. The second section discusses the implementation of edge AI for smart healthcare. The topics discussed in this section include, AR/VR and cloud computing, big data management, algorithms, optimization, and IoMT techniques and methods. Third section covers role of Edge-AI in healthcare and the challenges and opportunities of the technologies. This section also provides case studies and discusses sustainability, security, privacy, and trust related to Edge-AI in healthcare. This book is intended to benefit researchers, academics, industry professionals, R & D organizations and students working in the field of healthcare, healthcare informatics and their applications.

Computational Intelligence in Urban Infrastructure consolidates experiences and research results in computational intelligence and its applications in urban infrastructure. It discusses various techniques and application areas of smart urban infrastructure including topics related to smart city management. Major topics covered include smart home automation, intelligent lighting, smart human care services, intelligent transportation systems, ontologies in urban development domain, and intelligent monitoring, control, and security of critical infrastructure systems supported by case studies. Features: Covers application of AI and computational intelligence techniques in urban infrastructure planning Discusses characteristics and features of smart urban management Explores relationship between smart home and smart city management Deliberates various smart home techniques Includes different case studies for supporting and analyzing various aspects of smart urban infrastructure management This book is aimed at researchers, graduate students, libraries in communication networks, urban and town planning, and civil engineering.

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).

The use of artificial intelligence (AI) in various fields is of major importance to improve the use of resourses and time. This book provides an analysis of how AI is used in both the medical field and beyond. Topics that will be covered are bioinformatics, biostatistics, dentistry, diagnosis and prognosis, smart materials, and drug discovery as they intersect with AI. Also, an outlook of the future of an AI-assisted society will be explored.

Medical imaging has revolutionised the field of healthcare, providing critical insights and aiding in accurate diagnoses. This book, "Advanced Techniques in Medical Imaging: Computer Vision and Machine Learning Approaches," begins with an introduction to the world of medical imaging, highlighting its importance and evolution. We then delve into the fundamentals of computer vision, a key component in interpreting complex medical images. Following this, an introduction to machine learning sets the stage for understanding how these powerful algorithms can be harnessed to analyse medical data. The book covers a wide range of topics, including image segmentation techniques that allow for precise identification of structures within medical images and feature extraction and representation, which are crucial for converting image data into usable information. We explore medical image classification, illustrating how different algorithms can differentiate between various conditions. A significant portion of the book is dedicated to deep learning architectures, which have shown remarkable success in medical diagnosis. We also discuss computer-aided diagnosis systems, becoming indispensable tools for clinicians. Finally, the book addresses the challenges faced in this field. It looks towards future directions, ensuring that readers are equipped with a comprehensive understanding of the current landscape and the potential advancements in medical imaging technology. This book aims to provide a thorough grounding in the latest techniques and approaches, making it an invaluable resource for researchers, practitioners, and students involved in the intersection of medical imaging, computer vision, and machine learning.

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. - Offers advice on the development of state-of-the-art tech-driven healthcare systems and technologies for improving the quality of healthcare - Focuses on healthcare solutions that are inclusive and cost-effective - Discusses the future, limitations and challenges associated with the use and adoption of XR for healthcare

As the demand for advanced technologies to revolutionize patient care intensifies, the medical industry faces a pressing need to confront challenges hindering the assimilation of AI-enhanced healthcare systems. Issues such as data interoperability, ethical considerations, and the translation of AI advancements into practical clinical applications pose formidable hurdles that demand immediate attention. It is within this context of challenges and opportunities that the book, Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems promises to pave the way for a transformative era in healthcare. The book serves as a comprehensive guide for academic scholars, researchers, and healthcare professionals navigating the dynamic landscape of data-driven, AI-enhanced healthcare. By showcasing the latest advancements, the book empowers its readers to not only comprehend the existing frontiers in data sciences and healthcare technologies but also to actively contribute to overcoming obstacles. Through detailed case studies and practical guidance, the publication equips its audience with the skills necessary to implement AI in various clinical settings.

The Thinking Healthcare System: Artificial Intelligence and Human Equity is the first comprehensive book detailing the historical, global, and technical trends shaping the evolution of the modern healthcare system into its final form—an AI-driven thinking healthcare system, structured and functioning as a global digital health ecosystem. Written by the world's first triple doctorate trained physician-data scientist and ethicist, and author of three AI textbooks and over 350 scientific and ethics papers, this indispensable resource makes sense of how technology, economics, and ethics are already producing the future's health system—and how to ensure it works for every patient, community, and culture in our globalized, digitalized, and divided world. Providing clear descriptions and concrete examples, this book brings together AI-accelerated digital health ecosystems, data architecture, cloud and edge computing, precision medicine, public health, telemedicine, patient safety, health political economics, multicultural global ethics, blockchain, and quantum health computing, among other topics. Healthcare and business executives, clinicians, researchers, government leaders, policymakers, and students in the fields of healthcare management, data science, medicine, public health, informatics, health and public policy, political economics, and bioethics will find this book to be a groundbreaking resource on how to create, nourish, and lead AI-driven health systems for the future that can think, adapt, and so care in a manner worthy of the world's patients. - Details the first comprehensive, global, and multidisciplinary analysis of the AI-driven transformation of modern healthcare systems into their definitive digitalized form that will dominate the future - Provides clear descriptions and concrete examples of AI-informed value-based healthcare, digital health ecosystems, data architecture, cloud and edge computing, precision medicine, public health, telemedicine, patient safety, health political economics, multicultural and embedded global ethics, blockchain, AI security, health security, digital twins, and quantum health computing - Serves as a practical blueprint, roadmap, and system DNA for creating the future's healthcare system that integrates efficiency and equity to accelerate the treatment (and in some cases even cures) for some of our world's most urgent, immediate, and impending global health challenges and crises

This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics. Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems. Practical examples and case studies to help readers understand complex concepts. Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics. Clear and concise language that is easy to understand. This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.

Internet of things (IoT) applications employed for healthcare generate a huge amount of data that needs to be analyzed to produce the expected reports. To accomplish this task, a cloud-based analytical solution is ideal in order to generate faster reports in comparison to the traditional way. Given the current state of the world in which every day IoT devices are developed to provide healthcare solutions, it is essential to consider the mechanisms used to collect and analyze the data to provide thorough reports. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications applies artificial intelligence (AI) in edge analytics for healthcare applications, analyzes the impact of tools and techniques in edge analytics for healthcare, and discusses security solutions for edge analytics in healthcare IoT. Covering topics such as data analytics and next generation healthcare systems, it is ideal for researchers, academicians, technologists, IT specialists, data scientists, healthcare industries, IoT developers, data security analysts, educators, and students.