You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
This book discusses Internet of Things (IoT) as it relates to enterprise applications, systems, and infrastructures. The authors discuss IoT and how it’s disrupting industries such as enterprise manufacturing, enterprise transportation, enterprise smart market, enterprise utilities, and enterprise healthcare. They cover how IoT in the enterprise will have a major impact on the lives of consumers and professionals around the world and how it will change the way we think about professional and consumer networks. The book's topics include IoT enterprise system architecture, IoT enabling enterprise technologies, and IoT enterprise services and applications. Examples include enterprise on demand, market impacts, and implications on smart technologies, big data enterprise management, and future enterprise Internet design for various IoT use cases, such as share markets, healthcare, smart cities, smart environments, smart communications and smart homes.
Emerging technologies have become both crucibles and showrooms for the practical application of artificial intelligence, the internet of things, and cloud computing, and for integrating big data into everyday life. Is the digital world optimized and sustainable using intelligence systems, machine learning, and cyber security methods? This complex concoction of challenges requires new thinking of the synergistic utilization of intelligence systems, machine learning, deep learning and blockchain methods, data-driven decision-making with automation infrastructure, autonomous transportation, and connected buildings. Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery ...
Artificial intelligence models are being used to make labor and delivery safer for mothers and newborns. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. This is a critical area of study as maternal and infant health are indispensable for a healthy society. Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning considers the recent advances, challenges, and best practices of artificial intelligence and machine learning in relation to pregnancy complications. Covering key topics such as pregnancy complications, wearable sensors, and healthcare technologies, this premier reference source is ideal for nurses, doctors, computer scientists, medical professionals, industry professionals, researchers, academicians, scholars, instructors, and students.
The healthcare sector is at a critical juncture, facing the pressing need to integrate generative AI technologies responsibly. Despite the promising benefits, such as improved diagnostics, personalized treatments, and streamlined operations, the adoption of AI in healthcare poses significant challenges. These challenges include ethical dilemmas, regulatory complexities, and the need for governance frameworks to ensure the technology's responsible use. Revolutionizing the Healthcare Sector with AI offers a comprehensive solution to these challenges. It provides a deep dive into the adoption, integration, scalability, and sustainability of generative AI in healthcare and a thorough analysis of governance, ethical, and regulatory issues. By offering insights from researchers, practitioners, patients, and policymakers, this book is a platform for responsible AI adoption in healthcare.
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 deliver...
Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications, experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, suc...
In contemporary healthcare, Industry 5.0 technologies present a paradoxical challenge and opportunity. The rapid integration of Cyber Physical Systems, Cloud Computing, Internet of Things, Artificial Intelligence, Smart Factories, and Cognitive Computing has ushered in unprecedented transformations, yet it has concurrently given rise to critical vulnerabilities within healthcare systems. As sensitive patient data becomes increasingly digitized, the specter of cybersecurity threats looms larger than ever. The book, titled "Technologies for Sustainable Healthcare Development," undertakes the crucial task of addressing this pressing concern. Focused on Cybersecurity and Data Science Innovations...
The lack of comprehensive, innovative insights into the intricate world of pregnancy complication prediction is a pressing concern, as these complications can severely impact the health and wellbeing of pregnant patients. As the complexities of maternal healthcare continue to evolve, scholars grapple with the challenge of staying at the forefront of research and innovation in this critical field. The unpredictability of pregnancy complications poses significant risks to positive patient outcomes, demanding novel approaches to diagnosis and prevention. The academic community seeks a solution that can bridge the gap between traditional research and the transformative potential of technological...
In the field of computer vision research, the study of human behavior is a formidable challenge. The diverse applications of this field, from video surveillance for crowd analysis to healthcare diagnostics, have drawn increasing attention. However, a significant problem persists – the sacrifice of transparency for the sake of predictive accuracy in Artificial Intelligence (AI) solutions. These AI systems often operate as enigmatic black boxes, seemingly conjuring decisions from vast datasets with little to no explanation. The need for clarity and accountability in AI decision-making is paramount as our reliance on these systems continues to grow. Explainable AI Applications for Human Behav...
Intelligent systems, powered by artificial intelligence (AI) and machine learning, offer transformative benefits across diverse sectors, from healthcare and finance to manufacturing and agriculture. By refining these systems to be more adaptable, scalable, and informative, industries can solve complex business problems and streamline operations. Effective research into technical challenges across intelligent system application is necessary to prioritize their development and impact in industries, such as crop analysis, disease diagnosis, or traffic management. Optimizing Intelligent Systems for Cross-Industry Application explores the challenges and opportunities associated with intelligent t...