Exploring The Convergence Of Computer And Medical Science Through Cloud Healthcare

Digital technologies are currently dramatically changing healthcare. Cloud healthcare is an increasingly trending topic in the field, converging skills from computer and health science. This new strategy fosters the management of health data at a large scale and makes it easier for healthcare organizations to improve patient experience and health team productivity while helping the support, security, compliance, and interoperability of health data. Exploring the Convergence of Computer and Medical Science Through Cloud Healthcare is a reference in the ongoing digital transformation of the healthcare sector. It presents a comprehensive state-of-the-art approach to cloud internet of things health technologies and practices. It provides insights over strategies, methodologies, techniques, tools, and services based on emerging cloud digital health solutions to overcome digital health challenges. Covering topics such as auxiliary systems, the internet of medical things, and natural language processing, this premier reference source is an essential resource for medical professionals, hospital administrators, medical students, medical professors, libraries, researchers, and academicians.

This book reviews the convergence technologies like cloud computing, artificial intelligence (AI) and Internet of Things (IoT) in healthcare and how they can help all stakeholders in the healthcare sector. The book is a proficient guide on the relationship between AI, IoT and healthcare and gives examples into how IoT is changing all aspects of the healthcare industry. Topics include remote patient monitoring, the telemedicine ecosystem, pattern imaging analytics using AI, disease identification and diagnosis using AI, robotic surgery, prediction of epidemic outbreaks, and more. The contributors include applications and case studies across all areas of computational intelligence in healthcare data. The authors also include workflow in IoT-enabled healthcare technologies and explore privacy and security issues in healthcare-based IoT.

The integration of artificial intelligence (AI) stands as both a promise and a challenge in the field of healthcare. As technological advancements reshape the industry, academic scholars find themselves at the forefront of a crucial dialogue about the ethical implications and societal repercussions of AI. The accelerating sophistication of AI technologies brings forth a central dilemma: how to maintain the crucial human touch required for compassionate and effective patient care in the face of unprecedented technical progress. This challenge is not only a theoretical concern but a pressing reality as healthcare systems increasingly rely on AI-driven solutions. Approaches to Human-Centered AI in Healthcare emerges as a significant guide, offering a comprehensive exploration of the opportunities and challenges entwined with the integration of AI into healthcare. The book becomes a critical compass, navigating readers through the intricate intersections of AI and patient care. By delving into real-world case studies, cutting-edge research findings, and practical recommendations, it provides a roadmap for scholars to navigate the complexities of healthcare AI. In doing so, it aims not only to inform but to shape the discourse around the responsible integration of AI, ensuring that the fundamental principles of compassionate patient care remain at the forefront.

Bioinspiration is recognized by the World Health Organization as having great promise in transforming and democratizing health systems while improving the quality, safety, and efficiency of standard healthcare in order to offer patients the tremendous opportunity to take charge of their own health. This phenomenon can enable great medical breakthroughs by helping healthcare providers improve patient care, make accurate diagnoses, optimize treatment protocols, and more. Unfortunately, the consequences can be serious if those who finance, design, regulate, or use artificial intelligence (AI) technologies for health do not prioritize ethical principles and obligations in terms of human rights and preservation of the private life. Advanced Bioinspiration Methods for Healthcare Standards, Policies, and Reform is the fruit of the fusion of AI and medicine, which brings together the latest empirical research findings in the areas of AI, bioinspiration, law, ethics, and medicine. It assists professionals in optimizing the potential benefits of AI models and bioinspired algorithms in health issues while mitigating potential dangers by examining the complex issues and innovative solutions that are linked to healthcare standards, policies, and reform. Covering topics such as genetic algorithms, health surveillance cameras, and hybrid classification algorithms, this premier reference source is an excellent resource for AI specialists, hospital administrators, health professionals, healthcare scientists, students and educators of higher education, government officials, researchers, and academicians.

In a world characterized by complexity and rapid change, the intersection of healthcare, social sciences, and technology presents a formidable challenge. The vast array of interconnected issues, ethical dilemmas, and technological advancements often evade comprehensive understanding within individual disciplines. The problem lies in the siloed approach to these critical domains, hindering our ability to navigate the complexities of our modern world effectively. Change Dynamics in Healthcare, Technological Innovations, and Complex Scenarios emerges as a transformative solution, offering a beacon of insight and knowledge to those grappling with the intricate dynamics of our interconnected society. Change Dynamics in Healthcare, Technological Innovations, and Complex Scenarios dives into organizational narratives, ethical challenges, and technological promises across healthcare, social sciences, and technology. It doesn't merely acknowledge the interplay between these disciplines; it celebrates their interconnectedness. By dissecting, analyzing, and synthesizing critical developments, this book serves as a compass, providing a rich resource for comprehending the multifaceted impacts of emerging changes.

Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes. Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.

In the ancient world, health seekers traversed vast distances to pursue well-being. Fast forward to the 21st century, and the concept of medical tourism has evolved into a global industry worth billions of dollars. The burgeoning demand for quality healthcare has pushed traditional boundaries, necessitating a more sophisticated and interconnected healthcare ecosystem. Integrating Artificial Intelligence (AI) into medical practices empowers individuals to actively manage their health while providing healthcare practitioners with invaluable insights for tailored patient care. Impact of AI and Robotics on the Medical Tourism Industry delves into the transformative impact of AI and robotics on this dynamic sector. It explores how AI can encourage and assist patients in their health plans while augmenting healthcare practitioners' capabilities to utilize specific patient data to offer unique guidance. It dissects real-world examples, such as Cleveland Clinic Abu Dhabi's integration of robotic surgery, showcasing how these technologies revolutionize traditional medical practices.

In the wake of the digital healthcare revolution, a critical challenge has emerged: the lack of a comprehensive understanding stemming from fragmented research. Despite the industry's meteoric rise, existing literature often compartmentalizes insights, neglecting the intricate multi-sector collaborations that fuel its progress. This gap hinders scholars and industry professionals, leaving them with a myopic view of the digital healthcare landscape. The urgent need for a holistic exploration has never been more apparent. Multi-Sector Analysis of the Digital Healthcare Industry is a groundbreaking book that will uncover the complexities of digital healthcare with a panoramic lens. This carefully curated collection of cross-functional chapters is a beacon guiding academics and industry specialists through the difficulties of the industry's past, present, and future. With experts from fields spanning medicine, technology, business, and regulatory sectors, this book addresses the limitations of current research but serves as a compass for those seeking a more profound comprehension of digital healthcare's collaborative dynamics.