Achin Jain – författare
Visar alla böcker från författaren . Handla med fri frakt och snabb leverans.
4 produkter
4 produkter
Häftad, Engelska, 2026
1 773 kr
Skickas inom 10-15 vardagar
Explainable AI in Clinical Practice: Methods, Applications, and Implementation bridges the gap between artificial intelligence capabilities and their practical implementation in healthcare. The book explores applications of explainable AI in diagnostic support and treatment planning, offering insights into making AI systems interpretable and accountable. Through real-world case studies and ethical frameworks, readers learn to transform opaque AI systems into tools that enhance clinical practice while maintaining high patient care standards. This volume unites leading experts to provide a comprehensive framework for implementing explainable AI, ensuring that AI-driven decisions are transparent, trustworthy, and clinically sound. Targeted solutions in the book cater to diverse stakeholders in the healthcare AI ecosystem. Healthcare professionals will gain confidence in integrating AI tools, while technical teams will receive implementation guidelines. This book is essential for anyone seeking to responsibly and effectively navigate the complexities of AI in healthcare.Provides a comprehensive framework for implementing explainable AI in healthcare, ensuring that AI-driven decisions are transparent, trustworthy, and clinically soundIncludes real-world case studies that illustrate practical applications of explainable AIOffers targeted solutions for diverse stakeholders in the healthcare AI ecosystem
E-bok
Engelska, 20262 184 kr
Läs direkt efter köp
Explainable AI in Clinical Practice: Methods, Applications, and Implementation bridges the gap between artificial intelligence capabilities and their practical implementation in healthcare. The book explores applications of explainable AI in diagnostic support and treatment planning, offering insights into making AI systems interpretable and accountable. Through real-world case studies and ethical frameworks, readers learn to transform opaque AI systems into tools that enhance clinical practice while maintaining high patient care standards. This volume unites leading experts to provide a comprehensive framework for implementing explainable AI, ensuring that AI-driven decisions are transparent, trustworthy, and clinically sound. Targeted solutions in the book cater to diverse stakeholders in the healthcare AI ecosystem. Healthcare professionals will gain confidence in integrating AI tools, while technical teams will receive implementation guidelines. This book is essential for anyone seeking to responsibly and effectively navigate the complexities of AI in healthcare. - Provides a comprehensive framework for implementing explainable AI in healthcare, ensuring that AI-driven decisions are transparent, trustworthy, and clinically sound- Includes real-world case studies that illustrate practical applications of explainable AI- Offers targeted solutions for diverse stakeholders in the healthcare AI ecosystem
- Nyhet
Häftad, Engelska, 2026
1 875 kr
Skickas inom 10-15 vardagar
Explainable AI in Clinical Practice: Advanced Applications and Future Directions builds on foundational concepts to explore the practical implementation and emerging trends of transparent AI in healthcare. Featuring contributions from leading experts, this volume presents advanced methodologies, real-world case studies across various medical specialties, and strategies for overcoming ethical, regulatory, and operational challenges. The book offers comprehensive frameworks for integrating explainable AI into clinical workflows, emphasizing trust, patient understanding, and regulatory compliance. In addition, it examines future technologies such as federated learning, multimodal systems, and human-AI collaboration, providing insights into the evolving landscape of AI in medicine.Essential for healthcare professionals, researchers, and policymakers, this volume aims to accelerate the responsible adoption of explainable AI, ultimately enhancing patient care, clinical decision-making, and healthcare system efficiency.Provides comprehensive implementation frameworks that guide the deployment of explainable AI in healthcare, addressing technical, organizational, ethical, and regulatory challengesPresents detailed, specialty-specific case studies that demonstrate successful real-world applications of explainable AI across various clinical disciplinesExplores future directions and emerging technologies, offering insights into how explainable AI will integrate with innovations like federated learning and multimodal systems to shape healthcare’s evolution
- Nyhet
2 310 kr
Läs direkt efter köp
Explainable AI in Clinical Practice: Advanced Applications and Future Directions builds on foundational concepts to explore the practical implementation and emerging trends of transparent AI in healthcare. Featuring contributions from leading experts, this volume presents advanced methodologies, real-world case studies across various medical specialties, and strategies for overcoming ethical, regulatory, and operational challenges. The book offers comprehensive frameworks for integrating explainable AI into clinical workflows, emphasizing trust, patient understanding, and regulatory compliance. In addition, it examines future technologies such as federated learning, multimodal systems, and human-AI collaboration, providing insights into the evolving landscape of AI in medicine.Essential for healthcare professionals, researchers, and policymakers, this volume aims to accelerate the responsible adoption of explainable AI, ultimately enhancing patient care, clinical decision-making, and healthcare system efficiency. - Provides comprehensive implementation frameworks that guide the deployment of explainable AI in healthcare, addressing technical, organizational, ethical, and regulatory challenges- Presents detailed, specialty-specific case studies that demonstrate successful real-world applications of explainable AI across various clinical disciplines- Explores future directions and emerging technologies, offering insights into how explainable AI will integrate with innovations like federated learning and multimodal systems to shape healthcare's evolution