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In our contemporary era, while diversity is acknowledged, true inclusion remains an elusive goal, as society grapples with multifaceted challenges. The "great resignation" and movements like #MeToo have exposed workplace culture issues, while events like Black Lives Matter protests underscored glaring disparities. Simultaneously, rapid technological advancements introduce new risks, from cyber exploitation to biased AI. These complexities demand innovative solutions that address these challenges, fostering environments of genuine respect, understanding, and collaboration. Applied Research Approaches to Technology, Healthcare, and Business, edited by Dr. Darrell Norman Burrell, emerges as a transformative force. This dynamic anthology presents insights, research, and actionable recommendations from diverse fields and perspectives, taking an interdisciplinary approach to unravel workplace dynamics, health disparities, and technological advancements. Topics include inclusive leadership, equitable technology, bias in AI, and forging collaboration across religious and cultural differences. By harmonizing voices and expertise, this book offers transformative approaches for individuals, educators, and professionals. This rich resource empowers readers to navigate today's societal challenges, equipping them to become architects of a more inclusive, equitable, and harmonious future across technology, healthcare, and business.
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
Economically disadvantaged communities in many regions around the world are making concerted efforts to become integrated into the global information society. The adoption and use of an array of technology tools and services by these communities will pave the way for their inclusion. Adoption and Use of Technology Tools and Services by Economically Disadvantaged Communities: Implications for Growth and Sustainability examines the challenges facing economically disadvantaged communities with respect to their digital divide and emerging opportunities as they adopt modern ICT tools and services for growth and sustainability. Focus is given to research on ICT adoption, use, and impact on lives, businesses, and societies. Covering topics such as the digital divide, food traceability, and big data analytics, this premier reference source is an excellent resource for sociologists, government officials, community leaders, students and educators of higher education, librarians, researchers, and academicians.
Large Language Models (LLMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying advanced AI techniques to identify and predict weaknesses in software code, including zero-day exploits and complex malware, LLMs provide a proactive approach to securing digital environments. This integration of AI and cybersecurity presents new possibilities for enhancing software security measures. Application of Large Language Models (LLMs) for Software Vulnerability Detection offers a comprehensive exploration of this groundbreaking field. These chapters are designed to bridge the gap between AI research and practical application in cybersecurity, in order to provide valuable insights for researchers, AI specialists, software developers, and industry professionals. Through real-world examples and actionable strategies, the publication will drive innovation in vulnerability detection and set new standards for leveraging AI in cybersecurity.
In the rapidly evolving realm of Artificial Intelligence (AI) and digital technologies, a pressing issue confronts academic scholars and social scientists—the profound consequences of AI adoption within the intricate structures of society. Despite its pervasive influence, this critical topic remains largely unexplored in academic circles, leaving a significant knowledge gap regarding how AI reshapes human interactions, institutions, and the fabric of our digital society. AI and Emotions in Digital Society, edited by Adrian Scribano and Maximiliano E Korstanje, emerges as the timely and compelling solution to bridge this divide. In this transformative book, readers embark on an intellectual journey exploring the intricate interplay between society, technology, and emotions. Drawing together high-quality chapters from diverse disciplines and cultural backgrounds, the book fosters critical discussions that delve into the philosophical quandaries underpinning AI's influence, especially within the context of our ever-changing world. By adopting a balanced perspective that acknowledges both risks and opportunities, the book equips postgraduate students, professionals, policymakers, AI analysts, and social scientists with the tools to comprehend the far-reaching effects of AI on human behavior, institutions, and democratic processes. As readers engage with this thought-provoking content, they gain profound insights into how AI impacts various sectors, including education, travel, literature, politics, and cyber-security. AI and Emotions in Digital Society serves as an indispensable resource for navigating the ongoing AI revolution, inspiring informed decision-making, and fostering critical dialogue. By empowering readers to grasp the complexities of AI's role in a new cosmopolitan capitalism, the book opens possibilities for a future where humanity and technology harmoniously coexist, shaping the course of our digitally interconnected society.
Amid an unprecedented digital revolution, our society grapples with profound challenges, from the upheaval of traditional global systems to the ethical implications of technology's inexorable advance. As academic scholars seek a comprehensive understanding of this dynamic environment, Driving Decentralization and Disruption With Digital Technologies emerges as a beacon of insight. This compelling book confronts the intricate issues spawned by decentralization, de-globalization, and the transformative power of digital technologies, providing a roadmap for traversing the complexities of our digitally connected world. The book starts by unraveling the disruptive forces at play, shedding light on the threats posed to existing hierarchies and the potential consequences for disadvantaged groups. Digital disintermediation, driven by platforms and peer-to-peer networks, shakes the foundations of traditional economic systems, leaving banks and markets in flux. As global relationships redefine themselves in the face of decentralized markets, supply chains, and economic ties, scholars grapple with the profound implications for the future.
In the rapidly evolving digital landscape, the importance of cybersecurity has never been more critical. With the increasing sophistication of cyber threats, traditional security measures often fall short in providing adequate protection. Cyber artificial intelligence (AI) offers advanced capabilities to detect, prevent, and respond to attacks in real time. As cyber threats continue to grow in complexity and frequency, the integration of AI into cybersecurity frameworks is not just advantageous but essential for maintaining robust and resilient defenses. Redefining Security With Cyber AI delves into the profound transformation of security paradigms brought about by the advent of AI. This book explores the intricate dance between the ever-expanding frontiers of digital technology and the AI-driven mechanisms that aim to safeguard them. Covering topics such as artificial neural networks, intrusion detection, and large language models, this book is an excellent resource for cybersecurity professionals, AI and machine learning researchers, IT executives and managers, policy makers and regulators, postgraduate students and educators, academicians, and more.
The longstanding practice of keeping academic disciplines separate has been a barrier to effectively addressing the complex challenges in our world. The boundaries separating fields like healthcare, social sciences, and technology have obscured the potential for interdisciplinary collaboration, preventing us from unlocking innovative solutions to the most pressing issues of our time. As a result, the critical problems we face, from healthcare inequities to technological advancements with ethical dilemmas, have remained largely unresolved. This fragmented approach to academic inquiry has left a void in our quest to tackle these challenges effectively. The solution is found within the pages of Innovations, Securities, and Case Studies Across Healthcare, Business, and Technology. This groundbreaking compendium illuminates the transformative potential of interdisciplinary collaboration, offering direction and support in the form of knowledge for scholars, researchers, practitioners, and students committed to solving real-world problems. By harnessing the collective wisdom of diverse disciplines, the book demonstrates how convergence across healthcare, social sciences, organizational behavior, and technology can lead to groundbreaking insights and solutions. It showcases success stories and innovative strategies that drive positive change within our societies, offering a roadmap towards a brighter, more interconnected future.
In the realm of health care, privacy protections are needed to preserve patients' dignity and prevent possible harms. Ten years ago, to address these concerns as well as set guidelines for ethical health research, Congress called for a set of federal standards now known as the HIPAA Privacy Rule. In its 2009 report, Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research, the Institute of Medicine's Committee on Health Research and the Privacy of Health Information concludes that the HIPAA Privacy Rule does not protect privacy as well as it should, and that it impedes important health research.
"This book presents theoretical and empirical research on the value of information technology in healthcare"--Provided by publisher.