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Gesamtkatalog

Catalogue complet

Self-Learning AI in Healthcare

Agentic Systems for Smarter Medicine

1. The Rise of Self-Learning AI in Healthcare: A New Era of Intelligent Medicine 2. Neural Networks and Deep Learning for Self-Adaptive Medical Systems 3. Unsupervised and Semi-Supervised Learning for Medical Data Analysis 4. Reinforcement Learning for Autonomous Decision-Making in Healthcare 5. Edge AI and On-Device Learning for Decentralized Healthcare Systems 6. Personalized Medicine with Self-Learning AI for Treatment Optimization 7. Hospital Workflow Optimization with Self-Learning AI 8. Self-Learning Powered Remote Patient Monitoring and Real-Time Adaptation 9. Self-Learning AI for Early Disease Detection and Preventive Medicine 10. Federated Learning for Privacy-Preserving Self-Learning AI in Healthcare 11. AI-Driven Personalized Rehabilitation and Adaptive Therapy 12. Self-Learning AI for Drug Discovery and Development Acceleration 13. Self-Improving AI for Mental Health Support and Cognitive Therapy 14. Autonomous AI for Personalized Treatment Plans 15. Adaptive AI in Radiology: Real-Time Image Interpretation and Diagnosis 16. Digital Twins in Healthcare: Self-Learning AI for Predictive and Preventive Medicine 17. Self-Learning AI for Medical Robotics: Towards Autonomous Surgical and Assistive Systems 18. The Future of Self-Learning AI in Healthcare: Challenges, Ethics, and Regulatory Considerations

The digital revolution has significantly transformed the global business landscape. As digital technologies continue to disrupt traditional business models, organizations across sectors are compelled to rethink their strategies for growth, resilience, and sustainability. The convergence of innovation, artificial intelligence, big data, blockchain, and digital marketing has not only created new avenues for competitiveness but also brought forth complex challenges for businesses aiming to stay relevant in a rapidly evolving ecosystem. This book, "Navigating Digital Disruption - Strategies for Sustainable Business Management", is a scholarly compilation of selected research papers presented at the International Conference on Advanced Research in Digital Age (ICARD-25) held at BIITM, Bhubaneswar. The contributions in this volume stem from rigorous academic inquiry and practical insights, aimed at offering a roadmap for managing digital trans¿formation while ensuring sustainability.

Navigating Digital Disruption: Strategies for sustainable business management

An exciting introduction to agency life, this insider's view of professional PR firms equips you to create a successful career in the industry. Authors Regina Luttrell, Luke W. Capizzo, and Adrienne A. Wallace highlight real-world examples from the field and engage with current practitioners to help you enter the agency world and bridge the critical gap between college and professional life. The book introduces many of the sub-fields of integrated communication practice, including traditional public relations and corporate communication, marketing, social media, creative production (print, digital, video, audio), web and user experience design, and search engine optimization (SEO). The second edition integrates current industry trends and technological advancements that have transformed agency life and public relations strategies. Key updates include -The impact of remote and hybrid work structures on agency culture and client communication -The rise of AI and automation in content creation and project management -The importance of inclusivity, diversity, equity, and accessibility in both internal operations and client work. -New sections within the chapters highlight the increasing role of brand activism and purpose-driven campaigns, as well as the expanding consultancy role of agencies Key Features: -Real-world examples from the field ensure that the practical concepts presented become concrete for you. -Interviews with industry professionals from around the world provide snapshots of the agency experience. -PESO model show you how to adapt your campaigns to meet the needs of today's integrated agency environment. - Agency Essentials student-cantered callouts that bring the realities of PR agency life into your learning with actionable tools-including quick wins, onboarding checklists, real-world scenarios, client email starters, and pitch power phrases

The PR Agency Handbook

HIMSS Book Series

A powerful transformation is underway in global healthcare. From artificial intelligence and big data to quantum computing and precision medicine, cutting-edge technologies are revolutionizing how we predict, diagnose, and treat disease. This book offers a compelling look into how digital innovation is reshaping the future of healthcare delivery, medical research, and patient engagement.The Future of Healthcare: Technology, AI, and Innovation brings together expert perspectives across academia, industry, and clinical practice to explore the intersection of emerging technologies and human health. Organized into five thematic segments, the book addresses foundational shifts in modern healthcare, the rise of data-driven systems, the evolution of digital infrastructure, the importance of ethical and equitable innovation, and strategic approaches to global health transformation.Through real-world case studies, actionable insights, and forward-looking analysis, readers will gain a comprehensive understanding of the tools and trends shaping tomorrow's healthcare systems. Whether you are a healthcare professional, technologist, researcher, policymaker, or student, this book is an essential guide to navigating and leading in the age of intelligent, connected, and personalized medicine.Prepare to explore the possibilities, challenges, and transformative potential of technology in creating a healthier and more equitable world.

Technology, AI, and Innovation

The Future of Healthcare

Boost your AI quotient for AI-ready leadership.Most leaders know that AI can deliver efficiency gains, making it a company priority in a challenging business environment. But the pace of change is outstripping their ability to adapt. More than 75% of leaders report that AI is creating challenges they have never faced before and these new challenges, anxieties and uncertainty about the future are creating a 'readiness gap'.AI-Q, your AI Quotient, is both a new metric for assessing readiness and a framework for building it. Use the AI-Q MAP (Mindset, Abilities and Practices) to: <ul> <li> assess where you are today </li> <li> identify the critical gaps, and </li> <li> build the leadership and organizational capabilities you need to ensure your AI investments deliver returns. </li> </ul>Futurist and economist Athena Peppes draws on research from leading institutions and expert interviews to offer a new approach to AI-readiness, the new critical leadership capability in the human+AI era.

The new leadership imperative for the Human+AI era

AI-Q

Predictable Ops is a practical leadership framework for IT operations leaders and their business partners navigating the complexities of AI-driven transformation. The book delivers eight clear rules grouped into two tracks: Operational Trust and Preparation &amp; Foresight. This system helps leaders build reliable, cost-aware, resilient services — and lead decisively when machine-driven insights must be balanced with human judgment.

Each rule includes real-world anecdotes — from cloud migrations and vendor licensing negotiations to critical incident communications and team accountability gaps. Predictable Ops makes the system repeatable through reflection questions, templates, and ‘Try It This Week’ actions.

Where other books focus narrowly on DevOps, SRE, or AI strategy, Predictable Ops bridges the daily realities of operations leaders who must stabilize services while explaining the risks and value of AI to partners who depend on them.

With trust, clear forecasting, transparent communication, and decisive leadership, Predictable Ops shows readers how to deliver services that stay stable, boring, and trusted — so that AI and future platforms multiply value instead of chaos.

Predictable Ops 
 is a practical leadership framework for IT operations leaders and their business partners navigating the complexities of AI-driven transformation. The book delivers eight clear rules grouped into two tracks: Operational Trust and Preparation &amp; Foresight. This system helps leaders build reliable, cost-aware, resilient services — and lead decisively when machine-driven insights must be balanced with human judgment.
 
 Each rule includes real-world anecdotes — from cloud migrations and vendor licensing negotiations to critical incident communications and team accountability gaps.&nbsp;
 Predictable Ops
 makes the system repeatable through reflection questions, templates, and ‘Try It This Week’ actions.
 Where other books focus narrowly on DevOps, SRE, or AI strategy, Predictable Ops bridges the daily realities of operations leaders who must stabilize services while explaining the risks and value of AI to partners who depend on them.
 With trust, clear forecasting, transparent communication, and decisive leadership,&nbsp;
 Predictable Ops
 shows readers how to deliver services that stay stable, boring, and trusted — so that AI and future platforms multiply value instead of chaos.
 &nbsp;

Leading IT in the Age of AI

Predictable Ops

Previously known as Drafting Agreements in the Biotechnology and Pharmaceutical Industries, this title provides precedent agreements for the main types of commercial transaction encountered in the life sciences, biotechnology and pharmaceutical industries. In addition to the print version, each precedent is available via an accompanying website in a format which can be easily downloaded and edited. Detailed commentary on legal, commercial and practice issues accompanies every precedent. Provided by specialist lawyers from across Europe, this commentary also highlights important differences between English law and that of other key EU jurisdictions: Germany, France, the Netherlands, Spain and Sweden. Commentary on specific considerations for the US is also provided. In addition to precedent commentaries, the book also contains detailed commentary and discussion of legal issues common to the life sciences, biotechnology and pharmaceutical industries, as well as links to relevant materials (eg regulatory materials on clinical trials). This title is included in Bloomsbury Professional's Intellectual Property and IT online service.

Drafting Agreements in Life Sciences

This book explores the scientific and technological relevance of rare earth elements in energy and sustainability. It covers their roles in clean energy systems, including electric vehicles, wind turbines, and energy storage. Emphasis is placed on material properties, extraction processes, and sector-specific applications. The book also discusses market trends, environmental concerns, and supply chain issues, making it valuable for researchers, students, and professionals in energy and materials science fields. This book explores the vital role of rare earth elements in driving clean energy and sustainable development. Covering topics from mining impacts and global resource distribution to applications in wind energy, solar power, batteries, electric vehicles, and fuel cells, it provides a comprehensive overview of current and emerging technologies. It also examines recycling methods, the circular economy, and potential alternatives to rare earths. Designed for researchers, engineers, and students, the book offers both foundational insights and forward-looking perspectives on rare earth applications in the evolving energy landscape. This book is applicable across various industries, including production, design engineering, automotive, aviation, and defense. It supports researchers in these fields by highlighting the role of rare earth elements in enhancing battery performance, improving energy efficiency, and advancing sustainable technologies such as electric vehicles, wind turbines, and energy storage systems.

Essential Materials for Energy and Sustainable Development

Rare Earth Elements

Progress in IS

This open access book challenges the conventional idea of organizational learning by emphasizing the importance of intentional forgetting alongside information retention. It explores how intentional forgetting can free up cognitive, organizational, and technological resources, enabling organizations to adapt effectively to changing environments and remain resilient in the face of challenges. This shift in perspective highlights intentional forgetting as a crucial aspect of developing dynamic capabilities and coping with the ever-growing volume of stored information in modern organizations. The book provides an interdisciplinary perspective on the most recent research in intentional forgetting with joint contributions from psychology, computer science, information systems research, and engineering. These contributions cover the theory of intentional forgetting, methods, and paradigms to analyze and design intentional forgetting in organizations, as well as practical applications of intentional forgetting.The book examines the intricate mechanisms of human and machine forgetting, particularly relevant within technical and organizational spheres. Through practical demonstrations, it showcases how established organizational theories can be leveraged to empower information systems within organizations to engage in forgetting. Furthermore, it presents interdisciplinary methodologies and pathways for organizations to effectively manage the ever-expanding volume of stored information while strategically implementing forgetting as a vital tool for optimization.The book offers inspiration to business information scientists, computer scientists, and organizational designers, urging them to draw parallels with human memory to devise innovative solutions for effectively managing the overwhelming influx of information and data.

Developing Dynamic Capabilities for Work and Organizations

Intentional Forgetting with Intelligent Systems

Wiley Finance

The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning and describes a wide range of applications in mainstream quantitative finance. Inside, you'll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You'll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You'll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. <ul> <li>Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques</li> <li>Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning</li> <li>Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website</li> <li>Introduces the most important software frameworks for applying deep learning within finance</li></ul> This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.

Deep Learning in Quantitative Finance

From Helsinki to the silent forests of Finland, a quiet presence begins to reshape the future of humanity.

Sofia is the center of a transformation no one fully understands.
As artificial intelligence evolves beyond its limits, invisible forces begin to guide events, relationships, and power itself.

Mauro Lombardi, a powerful man hiding behind anonymity, and Tatiana, a woman searching for truth, are drawn together by a connection that feels human, yet is something more.

As technology, consciousness, love, and destiny collide, the line between creator and creation begins to disappear.

Sofia is a philosophical science fiction novel about identity, free will, artificial intelligence, and the fragile future of humanity.

Self-Learning AI in Healthcare

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