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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 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.
List of contents
Section I: Foundations1. Foundations of AI in Healthcare
2. Introduction to XAI in Healthcare
3. Understanding the Need for Transparency in Clinical AI
4. Theoretical Frameworks for XAI in Medicine
5. AI Bias and Fairness in Clinical Applications
6. Evaluation Frameworks for Healthcare XAI
Section II: Methods and Technologies7. XAI Techniques for Medical Image Analysis
8. Natural Language Processing in Clinical Documentation
9. Time Series Analysis for Patient Monitoring
10. Integration of Multiple Data Modalities
Section III: Clinical Applications11. XAI in Diagnostic Support Systems
12. Transparent AI for Treatment Planning
13. Risk Prediction and Preventive Care
14. Drug Discovery and Development
15. Performance Metrics and Quality Assurance
16. Integration with Clinical Workflows
Section IV: Ethical and Regulatory Considerations17. Ethics of Transparent AI in Healthcare
18. Privacy and Security Considerations
19. Regulatory Compliance and Standards
20. Patient Trust and Acceptance
Section V: Future Directions
21. Emerging Trends and Technologies
22. Challenges and Opportunities
23. Future Research Directions
