Explainable AI in Clinical Practice
Methods, Applications, and Implementation
Herausgeber: Panwar, Arvind; Cengiz, Korhan; Li, Aimin; Mallik, Saurav; Jain, Achin
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Erscheint vorauss. 1. April 2026
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Explainable AI in Clinical Practice: Methods, Applications, and Implementation delivers an essential roadmap for bridging advanced artificial intelligence technologies with real-world healthcare settings. As AI increasingly supports clinical decision-making, the demand for clarity and trust in these systems is paramount. This book assembles leading experts to present a robust framework that ensures AI-driven recommendations are transparent, interpretable, and grounded in solid clinical judgment. Through in-depth exploration of diagnostic support and treatment planning, readers gain practical s...
Explainable AI in Clinical Practice: Methods, Applications, and Implementation delivers an essential roadmap for bridging advanced artificial intelligence technologies with real-world healthcare settings. As AI increasingly supports clinical decision-making, the demand for clarity and trust in these systems is paramount. This book assembles leading experts to present a robust framework that ensures AI-driven recommendations are transparent, interpretable, and grounded in solid clinical judgment. Through in-depth exploration of diagnostic support and treatment planning, readers gain practical strategies for making AI tools understandable and accountable, supporting high-quality patient care and ethical standards throughout the process. In addition, the book provides real-world case studies and discusses ethical considerations to help readers transform opaque AI models into reliable healthcare assets. It offers targeted solutions for a broad range of stakeholders, including clinicians looking to confidently adopt AI and technical teams seeking clear implementation guidelines.
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