Full Description
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.
Contents
1. Foundations of AI in Healthcare
2. Sustainable Health Record System Using Artificial Intelligence with Blockchain Technology: A Recent Trends and Future Research Perspective
3. Unleashing the Hidden Potential of Metaverse in Healthcare: A Bibliometric Analysis and Future Research Agenda
4. Interpretability in Clinical Sentiment Analysis: A Comparative Study of LIME, SHAP, and Grad-CAM in Large Language Models
5. Enhancing Clinical Documentation Through Explainable AI-Driven Natural Language Processing (NLP): Improving Transparency, Accuracy, and Compliance in Medical Record-Keeping
6. Smart AI-Driven Treatment Planning: Transparency and Discovering New Innovations in the Modern Medical Field
7. An Integrated Framework for Dengue Fever Prediction Using CNN with SHAP
8. Atrial Fibrillation Classification Using Rectangular Pulse and Cascade Hybrid Multilayer Perceptron (CHMLP) Neural Network
9. Cascade Hybrid Multilayer Perceptron Network for ECG Signal Pattern Recognition Applications
10. Interpretable Artificial Intelligence for Medical Imaging and Diagnostics
11. Leveraging Data Analytics for Better Patient Care and Operational Effectiveness in Hospitals
12. Smart Therapeutic Systems: The Role of Artificial Intelligence in Personalized Mental Health Care and Patient Supervision
13. Explainable AI for Malaria Classification: Enhancing Transparency and Trust in Clinical Diagnostics
14. Transparency in AI-Driven Healthcare: The Role of XAI in Enhancing Fairness and Mitigating Bias in Clinical Practice
15. The Transparent Heart: XAI in Cardiology
16. IoT-Enabled Smart Healthcare for Multiple Sclerosis: Trends, Challenges, and Future Directions
17. Self-guided Medication System using Hybrid Model of Graph Neural Networks with LIME
18. AI Bias & Fairness in Clinical Applications
19. Enhancing Trust in Deep Learning Diagnostics: The Role of Explainable AI in Medical Image Analysis
20. Emerging Trends in Artificial Intelligence in Drug Design and Development: Revolutionizing Clinical Practices
21. Emerging Trends and Technologies in Explainable AI (XAI) for Clinical Practice
22. Ethic of Transparant AI in Physiotherapy
23. Future Research Opportunities Towards Using XAI in Healthcare
