Artificial intelligence (AI) has emerged as a transformative force across various domains, revolutionizing the way we perceive and address challenges in healthcare. The convergence of AI and healthcare holds immense promise, offering unprecedented opportunities to enhance medical diagnosis, treatment, and patient care. In today’s world, the intersection of AI and healthcare stands as one of the most promising frontiers for innovation and progress. Artificial Intelligence Transformations for Healthcare Applications: Medical Diagnosis, Treatment, and Patient Care embodies this convergence, offering a comprehensive exploration of how AI is revolutionizing various aspects of healthcare delivery. At its core, this book addresses the urgent need for more effective and efficient healthcare solutions in an increasingly complex and data-rich environment. Covering topics such as chronic disease, image classification, and precision medicine, this book is an essential resource for healthcare professionals, medical researchers, AI and machine learning specialists, healthcare administrators and executives, medical educators and students, biomedical engineers, healthcare IT professionals, policy makers and regulators, academicians, and more.

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.

The current healthcare system faces complications including data acquisition, interpretation, and delivery challenges, particularly in out-of-hospital scenarios. The shortage of medical resources intensifies the demand for efficient information gathering and processing. Moreover, the potential of pervasive computing still needs to be explored in healthcare, limiting the industry's ability to leverage innovations like artificial intelligence, augmented reality, and virtual reality. Ubiquitous Computing and Technological Innovation for Universal Healthcare addresses the medical field's critical challenges. It presents innovative solutions grounded in the marriage of Unmanned Aerial Vehicles (UAV), pervasive computing, and metaverse intelligence. It outlines how these UAVs redefine out-of-hospital care, addressing the pressing need for efficient data collection and interpretation amid a global medical shortage. Integrating cognitive algorithms is explored to automate diagnosis and enhance healthcare systems' emergency responsiveness. The book revolves around developing and integrating treatment programs leveraging UAV communication. Topics such as artificial intelligence, telemedicine, blockchain, digital twins, augmented reality, and virtual reality are delved into for their role in creating intelligent healthcare systems. The focus on rapid identification of underlying health issues, real-time monitoring in the metaverse, and the economic, social, and environmental impact of these systems adds depth to the discourse. Structured as a vital resource for researchers, academicians, industry professionals, policy-makers, and system designers, this book bridges the gap between theory and application.

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This book examines the fundamental concepts and principles of digital transformation and AI, including their historical development, and underlying technologies, and analyzes the opportunities arising from digital transformation and AI in different sectors, such as healthcare, finance, education, transportation, and governance. It provides a comprehensive overview of digital transformation and AI technologies and their current state of implementation. It also explores the potential challenges and risks associated with digital transformation and AI, including ethical considerations, job displacement, privacy concerns, biases, impact on inequality, social interactions, and the overall well-being of individuals and communities. Additionally, the books provides and discusses policy and regulatory frameworks that can effectively address the opportunities and challenges posed by digital transformation and AI leading to responsible AI. It also delves into impact of automation on the job market and workforce. The book concludes by proposing potential strategies for navigating opportunities and challenges of digital transformation and AI integration. It emphasizes the need for interdisciplinary collaboration among stakeholders, including policymakers, industry leaders, academia, and civil society, to develop a comprehensive approach towards harnessing the full potential of digital transformation and AI and associated technologies. The book employs a multidisciplinary approach, drawing from various fields such as computer science, sociology, philosophy, political science, economics, law and governance. It combines theoretical analysis, empirical case studies, and expert perspectives to provide a holistic view of the subject matter. This book caters to a diverse audience, including students, researchers, academics, policymakers, industry professionals, and technology enthusiasts. It provides a valuable resource for those seeking a comprehensive understanding ofthe opportunities and challenges arising from the integration of digital transformation and AI in society.

Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

The integration of artificial intelligence (AI), quantum computing, and semiconductor technology offers improved innovation to redefine computational power and capabilities. As AI drives advances in machine learning and data processing, quantum computing revolutionizes problem-solving with its ability to handle complex calculations at improved speeds. Advancements in semiconductor technology push the limits of processing efficiency and miniaturization. Continued exploration on this convergence may accelerate breakthroughs in various fields such as cryptography, material science, and healthcare. Integration of AI, Quantum Computing, and Semiconductor Technology explores the intersection of artificial intelligence (AI) and semiconductor technology within the context of quantum computing. It offers a comprehensive analysis of the current advancements, challenges, and potential applications resulting from this convergence. This book covers topics such as cyber security, healthcare monitoring, and machine learning, and is a useful resource for computer engineers, energy scientists, business owners, healthcare administrators, environmental scientists, academicians, and researchers.

This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.

This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Authored by a leading voice in the field, Machine Learning for Healthcare provides a gateway to revolutionize the understanding of medicine and patient care. The book unlocks the secrets of clinical data, harnessing the power of machine learning to diagnose diseases with unprecedented accuracy, and predicting patient outcomes with confidence. From the intricacies of disease progression to the human factors shaping healthcare delivery, each chapter is a testament to the transformative potential of AI in medicine. Readers include anyone passionate about the intersection of technology and human well-being from healthcare professionals eager to stay ahead of the curve, to bystanders fascinated by the possibilities of AI.