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 the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.

The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. Digital Twins and Healthcare: Trends, Techniques, and Challenges facilitates the advancement and knowledge dissemination in methodologies and applications of digital twins in the healthcare and medicine fields. This book raises interest and awareness of the uses of digital twins in healthcare in the research community. Covering topics such as deep neural network, edge computing, and transfer learning method, this premier reference source is an essential resource for hospital administrators, pharmacists, medical professionals, IT consultants, students and educators of higher education, librarians, and researchers.

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.

The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.

In central banking, the need for effective governance and policy transformations has never been more pressing. Central banks serve as the bedrock of a nation's financial stability, and yet, they face an array of complex challenges in the modern era. The delicate balance between autonomy from government influence and the necessity of adapting to external economic forces has become increasingly elusive. As the world grapples with the aftermath of a global pandemic and persistent economic turbulence, the demand for innovative strategies to safeguard economic and financial stability has reached a crescendo. Central bankers, economists, and policy experts are left grappling with the daunting task of navigating these treacherous waters, in dire need of a compass to guide them toward a resilient future. Governance and Policy Transformations in Central Banking is a groundbreaking book that transcends traditional boundaries to offer a comprehensive solution to the complex challenges faced by central banks worldwide. This book not only diagnoses problems, it also presents a meticulously curated collection of new empirical and theoretical chapters that illuminate the path forward. It is an invaluable resource that empowers central banks with the knowledge and tools necessary for development, governance, and policy transformation.

Women around the world are dealing with hormone and menstrual problems; evidence linking high levels of menstrual distress to harmful health effects continues to emerge. Premenstrual, or late luteal, menstrual misery is quite frequent, with many women reporting physiological and psychological symptoms linked with it. Additionally, hormonal changes during the menstrual cycle have been linked to a variety of unpleasant mental and physical symptoms. Further study on the many challenges and health concerns associated with menstrual and premenstrual distress is required to provide women with appropriate support and treatment. Perspectives on Coping Strategies for Menstrual and Premenstrual Distress sheds light on the various distress tolerance approaches and coping strategies during menstrual and premenstrual phases and highlights some of the contemporary issues and problems faced by women in today’s era. Covering key topics such as alternative medicine, stressors, menstrual health, and cognitive coping, this reference work is ideal for healthcare professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

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.

A chasm grows between the currently established knowledge and the rapidly evolving landscape of healthcare. As the field of biomedical research hurtles forward with groundbreaking discoveries and transformative technologies, academic scholars find themselves grappling with a significant dilemma. There exists a disconnect between traditional educational resources and the need to keep pace with the latest innovations that are reshaping medicine, diagnosis, and treatment. This widening gap inhibits scholars from adequately preparing their students and hampers their ability to engage in relevant, cutting-edge research, ultimately impeding the advancement of healthcare as a whole. Biomedical Research Developments for Improved Healthcare serves as the ultimate solution to this academic challenge. This book offers a compelling bridge between the realm of academic theory and the dynamic world of practical, real-world biomedical research. Its primary objective is to equip scholars with the knowledge, insights, and materials needed to inspire the next generation of healthcare professionals. By presenting a comprehensive overview of the most recent and groundbreaking advancements in biomedical research, the book enables scholars to transcend the limitations of traditional academia and empower their students with up-to-date, practical knowledge.

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.