The use of technology in health sciences has a direct impact on health outcomes, as well as on the quality and the safety of healthcare processes. In addition, the use of new technological developments in medical education has proven to be greatly effective and creates realistic learning environments to experience procedures and devices that will become common in medical practice. However, bringing new technologies into the health sector is a complex task, which is why a comprehensive vision of the health sciences ecosystem (encompassing many different areas of research) is vital. Technological Adoption and Trends in Health Sciences Teaching, Learning, and Practice obtains an overview of the technological trends within the health sciences ecosystem, identifies the strengths and weaknesses of the research presented to date, and depicts possible future research directions within health science education and practice. Covering topics such as artificial intelligence and online laboratories, it is ideal for health sciences educators and practitioners, technological solution providers, health organizations, health and care workers, regulators, governing bodies, researchers, academicians, and students.

The pervasiveness of technology today has brought with it a bevy of ethical questions, many of which are difficult to answer. Average consumers place themselves at risk financially, professionally, and personally by everyday activities executed on computers and smartphones, and therein lies the responsibility of technologists and decision-makers to devise logical and ethical solutions. Exploring Ethical Problems in Today’s Technological World focuses on ethical dilemmas created by today's ever-changing technologies and how these issues have affected individuals, companies, and society. The book further explores key areas such as policies, abuses, consequences, and responsibilities of different technologies and their users. Covering topics such as hackers, smart homes, privacy, and social networking, this reference work is ideal for ethicists, computer scientists, policymakers, industry professionals, researchers, academicians, practitioners, and students studying ethics, law, security, human-computer interaction, and computer science.

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.

Despite remarkable advancements in biomedical research, the healthcare industry faces challenges in effectively translating these discoveries into tangible patient benefits. Healthcare professionals often need help to keep pace with the rapid evolution of medical knowledge, leading to variations in patient care and treatment outcomes. Policymakers and educators may need more insight to leverage recent biomedical developments in shaping effective health policies and educational curricula. Additionally, ethical considerations surrounding emerging technologies like gene editing and Artificial Intelligence (AI) in healthcare pose complex dilemmas that require careful navigation. Reshaping Healthcare with Cutting-Edge Biomedical Advancements offers a comprehensive solution to these challenges. By providing a detailed exploration of the latest breakthroughs in genomics, regenerative therapies, neurobiology, AI, and more, this book equips healthcare professionals with the knowledge needed to make informed decisions about patient care. It also guides policymakers and educators, offering insights into the implications of recent biomedical advancements for shaping health policies and educational programs.

Despite significant demand for healthcare professionals in the workforce, admission to health professional graduate programs is highly competitive with less than half of all medical school applicants gaining admission annually. The application process is nuanced, complex, and costly, which can often be a significant barrier to otherwise highly qualified students, particularly those from backgrounds underrepresented in the healthcare workforce. Further understanding of the best practices in navigating the application processes, academia, and professional development is crucial for those advising pre-health students. The Handbook of Research on Advising and Developing the Pre-Health Professional Student considers current practices and research regarding academic and extracurricular preparation of undergraduate students who wish to enter health professions and offers new pre-health professional advisors as well as more seasoned advisors and other administrators a resource to assist them in their professional journey. Covering a range of topics such as advisor relationships and lifelong learning skills, this major reference work is ideal for advisors, healthcare professionals, academicians, researchers, practitioners, scholars, instructors, and students.

Establishing the means to improve performance in healthy, clinical, and military populations has long been a focus of study in the psychological and brain sciences. However, a major obstacle to this goal is generating individualized performance phenotypes that allow for the design of interventions that are tailored to the specific needs of the individual. Recent developments in artificial intelligence (AI) have qualified for the development of precision approaches that consider individual differences, allowing, for example, the establishment of individualized training, preparation, and recuperation programs optimal for an individual’s cognitive and biological phenotype. Corollary developments in AI have proven that combining domain expertise and stakeholder insights can considerably improve AI’s quality, performance, and dependability in the psychology and brain sciences. Recent Developments in Machine and Human Intelligence studies original empirical work, literature reviews, and methodological papers that establish and validate precision AI methods for human performance optimization with a focus on modeling individual differences via state-of-the-art computational methods and investigating how domain expertise and human judgment can improve the performance of AI methods. The topics are crafted in such a way as to cover all the areas of artificial and human intelligence that require AI for further development. This book contains algorithms and techniques that are explained with the help of developed source code and encompasses the readiness and needs for advancements in managing yet another pandemic in the future. It is designed for academicians, scientists, research scholars, professors, graduates, undergraduates, and students.