?Artificial intelligence, Big data, Blockchain and 5G for Digital Transformation of Healthcare Industry provides insights on the successes and failures in the field of IT and digital health during the pandemic and analyzes the lessons from these cases. The social and economic recovery after the pandemic requires urgent solutions for citizens, companies and economies around the world. From research centers, labs, hospitals and academia, researchers and academics are working collaboratively to explore new views and frameworks to develop solutions for emergent problems. Artificial intelligence, Big data, blockchain and 5G for digital transformation of healthcare industry includes cases highlighting the application of digital healthcare solutions from around the world. In 23 Chapters this book delivers a collection of relevant innovative research on digital healthcare, with a three mains goals: 1) study the successes and failures in the field of IT and digital health during the pandemic, and analyze the lessons from these cases; 2) discuss the latest advances in the field of digital healthcare, with a special focus on Artificial Intelligence, Big Data, Blockchain and 5G; and 3) discuss implications for main stakeholders (patients, doctors, IT experts, directors, policy managers. The global outbreak caused by covid-19 caused global disruption in societies, healthcare systems, and economies around the world. This book provides insight to Researchers, clinicians, CEOs and policy makers who need to learn from the failures and successes and exploit the potential of advanced information technologies to build stronger healthcare systems, better quality healthcare services, and more resilient societies. Delivers a collection of relevant innovative research on digital healthcare Discusses the latest advances in the field of digital healthcare, with a special focus on Artificial Intelligence, Big Data, Blockchain, and 5G Provides current lessons learned from the pandemic Includes case studies and experiences from around the world, including Asia, Europe, Gulf Region, Latin America, the United States, and more

The book emphasizes the role of data in driving healthcare transformation, providing readers with a roadmap for understanding and effectively implementing data-driven innovations. It delves into the applications of big data analytics, unveiling valuable insights and offering real-time decision support to healthcare professionals and goes on to review the role of machine learning and artificial intelligence in enabling accurate diagnosis, personalized treatment recommendations, and predictive modeling. The book is an invaluable resource for healthcare professionals, researchers, policymakers, and technology enthusiasts alike. Its practical insights and perspectives empower stakeholders to leverage data-driven technologies effectively, thus fostering continuous improvements in patient care and shaping a brighter future for the healthcare industry as a whole.

Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.

In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of this challenge. Designed for academics, researchers, healthcare professionals, and stakeholders in Healthcare Industry 4.0, this book serves as a source of innovation. It not only illuminates the complexities of computational intelligence in healthcare but also provides a roadmap for overcoming the limitations posed by small sample sizes. From fundamental principles to innovative concepts, this book offers a holistic perspective, shaping the future of healthcare through the lens of computational intelligence and Healthcare Industry 4.0.

Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.

In the face of an evolving global landscape characterized by climate change and a pressing need for sustainable development, the finance sector remains at a critical juncture. Traditional financial models struggle to address the challenges posed by the transition to a low-carbon economy, and unlocking private investments for sustainable initiatives remains an uphill battle. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into financial systems presents both promise and peril, with the potential to reshape the industry while posing unprecedented challenges. Issues of Sustainability in AI and New-Age Thematic Investing is a beacon of insight and solutions in the realm of green finance and AI/ML integration. Geared toward academic scholars, policymakers, and industry experts, this book serves as a comprehensive guide to navigating the intricacies of sustainable development and energy transition. By highlighting the pivotal role of AI/ML in green finance, the publication bridges the gap between theoretical understanding and practical implementation, offering actionable solutions for unlocking private investments.

The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies. Features: Blockchain and internet of things in healthcare systems Secure Digital Health Data Management in Internet of Things Public Perception towards AI-Driven Healthcare Security, privacy issues and challenges in adoption of smart digital healthcare Big data analytics and Internet of things in the pandemic era Clinical challenges for digital health revolution Artificial intelligence for advanced healthcare Future Trajectory of Healthcare with Artificial Intelligence 9 Parkinson disease pre-diagnosis using smart technologies Emerging technologies to combat the COVID-19 Machine Learning and Internet of Things in Digital Health Transformation Effective Remote Healthcare and Telemedicine Approaches Legal implication of blockchain technology in public health This Book on "Digital Health Transformation with Blockchain and Artificial Intelligence" aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of secured healthcare data analytics. It can also be used as a textbook for a Masters course in security and biomedical engineering. This book will also present new methods for the medical data analytics, blockchain technology, and diagnosis of different diseases to improve the quality of life in general, and better integration into digital healthcare.

Industry 5.0 is advancing the collaboration between humans and machines and is finding value through connected virtual and human experiences. This technological revolution benefits numerous fields; however, the library and information science industry in particular can evolve and expand by embracing Industry 5.0. The Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0 considers the current research and future trends of technological advances in library and information science related to Industry 5.0. Covering key topics such as robotics, smart libraries, augmented reality, digital libraries, and artificial intelligence, this major reference work is ideal for librarians, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Data is the basic ingredient of all Big Data applications, and Big Data technologies are constantly deploying new strategies to maximise efficiency and reduce the time taken to process information. This book presents the proceedings of MMBD2022, the third edition of the conference series Modern Management based on Big Data (MMBD). The conference was originally scheduled to take place from 15 to 18 August 2022 in Seoul, South Korea, but was changed to a virtual event on the same dates. Some 200 submissions were received for presentation at the conference, 52 of which were ultimately accepted after exhaustive review by members of the programme committee and peer-reviewers, who took into account the breadth and depth of the research topics and the scope of MMBD. Topics covered include data analytics, modelling, technologies and visualization, architectures for parallel processing systems, data mining tools and techniques, machine learning algorithms, and big data for engineering applications. There are also papers covering modern management, including topics such as strategy, decision making, manufacturing and logistics-based systems, engineering economy, information systems and law-based information treatment, and papers from a special session covering big data in manufacturing, retail, healthcare, accounting, banking, education, global trading, and e-commerce. Big data analysis and emerging applications were popular topics. The book includes many innovative and original ideas, as well as results of general significance, all supported by clear and rigorous reasoning and compelling evidence and methods, and will be of interest to all those working with Big Data.