Exploring The Convergence Of Computer And Medical Science Through Cloud Healthcare

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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.
Approaches to Human-Centered AI in Healthcare

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.
Advanced Bioinspiration Methods for Healthcare Standards, Policies, and Reform

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.