Intelligent technologies have vastly improved the efficiency of healthcare industries and intersections of law and governance. Computational intelligence provides effective tools for data management, contract analysis, legal research, and algorithm development. However, with the integration of computational intelligence in health governance, considerable legal concerns beg further exploration. Intersections of Law and Computational Intelligence in Health Governance examines computational intelligence related to healthcare and governance approaches. It addresses issues of healthcare data analysis and storage by presenting solutions using medical computational intelligence techniques. This book covers topics such as healthcare accessibility, medical law, deep learning, and drug discovery and classification, and is a valuable resource for lawyers, policy makers, healthcare workers, medical professionals, academicians, and researchers.

Intelligent technologies have vastly improved the efficiency of healthcare industries and intersections of law and governance. Computational intelligence provides effective tools for data management, contract analysis, legal research, and algorithm development. However, with the integration of computational intelligence in health governance, considerable legal concerns beg further exploration. Intersections of Law and Computational Intelligence in Health Governance examines computational intelligence related to healthcare and governance approaches. It addresses issues of healthcare data analysis and storage by presenting solutions using medical computational intelligence techniques. This book covers topics such as healthcare accessibility, medical law, deep learning, and drug discovery and classification, and is a valuable resource for lawyers, policy makers, healthcare workers, medical professionals, academicians, and researchers.

This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

This collection draws upon a range of thematic and regional case studies and uses the right to health as a normative framework to explore the devastating impact of the COVID-19 pandemic in Africa. Drawing lessons from across the continent, the book discusses the challenges faced by African states seeking to ensure the availability, accessibility, and quality of health care in the context of the COVID-19 pandemic. In particular, the volume explores the impact of the pandemic on the right to health of vulnerable and marginalized groups, such as women, children, elderly persons with disabilities, refugees and asylum seekers, and people from disadvantaged communities. Due to the poor funding of the healthcare systems, access to health-related services was limited to these groups in many African countries, thereby leading to avoidable COVID-19-related deaths through shortages of vital supplies, including diagnostic tests, ventilators, and oxygen cylinders. Chapters in the volume also explore the contentious issues of vaccine mandates, equity, resource allocation, and the rights of healthcare providers during the pandemic. This collection will be of interest to students of public health, human rights, and the social sciences, as well as to academics and policymakers with an interest in the nexus between the COVID-19 pandemic and public health policy in Africa.

In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success.

This volume provides an interdisciplinary collection of essays from leaders in various fields addressing the current and future challenges arising from the implementation of AI in brain and mental health. Artificial Intelligence (AI) has the potential to transform health care and improve biomedical research. While the potential of AI in brain and mental health is tremendous, its ethical, regulatory and social impacts have not been assessed in a comprehensive and systemic way. The volume is structured according to three main sections, each of them focusing on different types of AI technologies. Part 1, Big Data and Automated Learning: Scientific and Ethical Considerations, specifically addresses issues arising from the use of AI software, especially machine learning, in the clinical context or for therapeutic applications. Part 2, AI for Digital Mental Health and Assistive Robotics: Philosophical and Regulatory Challenges, examines philosophical, ethical and regulatory issues arising from the use of an array of technologies beyond the clinical context. In the final section of the volume, Part 3 entitled AI in Neuroscience and Neurotechnology: Ethical, Social and Policy Issues, contributions examine some of the implications of AI in neuroscience and neurotechnology and the regulatory gaps or ambiguities that could potentially hamper the responsible development and implementation of AI solutions in brain and mental health. In light of its comprehensiveness and multi-disciplinary character, this book marks an important milestone in the public understanding of the ethics of AI in brain and mental health and provides a useful resource for any future investigation in this crucial and rapidly evolving area of AI application. The book is of interest to a wide audience in neuroethics, robotics, computer science, neuroscience, psychiatry and mental health.

Artificial Intelligence (AI) is swiftly reshaping global regulatory frameworks, and current discussions on privacy have been thrust into the limelight. The virtual spaces we inhabit and technological advancements demand reevaluating our understanding of privacy, freedom of expression, and access to information. As the world grapples with unprecedented digital transformation, intensified by the global pandemic, exploring the human impact of AI has never been more important. The book, Intersections Between Rights and Technology explores this juncture, dissecting the intricate relationship between the rights we hold dear and the transformative power of technology. This book navigates the complexities of safeguarding human rights in the digital realm with a multidisciplinary lens. Addressing issues of paramount importance—privacy, human dignity, personal safety, and non-discrimination—the book critically examines the evolving landscape and the necessity to recalibrate legal and societal norms. This book is an indispensable resource for scholars, policymakers, law enforcement professionals, and individuals passionate about shaping a digital world where rights are not just respected but actively protected.

Responsible and Explainable Artificial Intelligence in Healthcare: Ethics and Transparency at the Intersection provides clear guidance on building trustworthy Artificial Intelligence systems for healthcare. The book focuses on using Artificial Intelligence to improve diagnosis, prevent diseases, and personalize patient care. It addresses potential drawbacks, like reduced human interaction and ethical concerns, offering solutions for ethical and transparent Artificial Intelligence use in medicine. Across eight chapters, the book explores Artificial Intelligence's current status, its importance, and associated risks in healthcare. It explains designing reliable Artificial Intelligence for healthcare, tackling biases, and safeguarding patient privacy in the age of big data. The legal and regulatory landscape is also covered. One chapter is dedicated to showcasing real-world examples of responsible Artificial Intelligence in healthcare, highlighting best practices. The book concludes by summarizing key takeaways and discussing future challenges. "Responsible and Explainable Artificial Intelligence in Healthcare: Ethics and Transparency at the Intersection" is a valuable resource for healthcare professionals, policymakers, computer scientists, and ethicists concerned about Artificial Intelligence's ethical and societal impact on medicine. - Gives insights into the responsible and explainable use of Artificial Intelligence in healthcare and explore the challenges and opportunities for promoting ethical and transparent practices in this field - Offers the solution to strike a balance between patient privacy and data exchange - Provides concrete advice on how to create trustworthy, accountable, and transparent Artificial Intelligence systems - Explains the moral and social effects of Artificial intelligence in healthcare and suggests ways to encourage its ethical application