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Gesamtkatalog

Catalogue complet

Kataria A: Explainable AI for Healthcare

Explainable AI for Healthcare

Real-life Applications and Use- Cases for Practitioners

2. Understanding the Framework of Explainable AI in Healthcare 3. The Role of Transparency and Interpretability in Healthcare AI 4. Ethical Considerations in Implementing Explainable AI in Healthcare 5. Advancing Healthcare with Explainable AI: Enhancing Patient Monitoring and Outcomes 6. Navigating Interpretability in AI: Balancing Performance, Standards, and Practical Guidance 7. Applications of Explainable AI in Diagnosis and Treatment 8. Challenges and Solutions in Deploying Explainable AI in Smart Healthcare Systems 9. Case Studies: Real-world Examples of Explainable AI in Healthcare 10. Future Directions and Innovations in Explainable AI for HealthcareAppendix -A

Embedded System and GUI Development using MATLAB for Engineering Applications

Combining Human Thinking and Creativity with Technology to Inspire Audiences

Authentic Marketing

A How-To Guide for Implementation and Management

AI for Public Relations

Discover how to use AI confidently, responsibly and ethically as an HR practitioner with this practical jargon-free guide.

Understand How to Use Artificial Intelligence in Your HR Role

AI for People Professionals

Digital Culture & Society

Technologies and technological futures are always socially situated, relational, and enmeshed in (dominant) narratives of societal sense-making, which have the power to bring future ideas into material existence. The issue brings together articles exploring popular techno-futures from international and interdisciplinary perspectives, including cultural and media studies, science and technology studies, and related disciplines. The contributors decenter the discussion on socio-technical futures and the role of popular culture, aesthetics and media in their (re)production by focusing on societal tech-future discourses from global popular perspectives.

Vol. 11, Issue 2/2025 – Towards Popular Techno-Futures: A Global Culture Perspective

Digital Culture & Society (DCS)

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Medical Robots and Devices: New Developments and Advances

AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies. The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

AI and Data Science in Medical Research

Six Dimensions of Business Dark Data

Agentic Hyper-Personalized Dimensions

Manage the complexity of AI in any organization with this actionable guide to operationalizing AI governance, navigating regulatory challenges and future-proofing systems.

Building a Program for Strategy and Oversight

Practical AI Governance

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

Artificial Intelligence and Machine Learning in Data Science and Analytics

Machine Learning For Dummies

Explainable AI for Healthcare

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