Full Description
This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis.
This book:
• Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications.
• Covers explainable AI for robotics and autonomous systems.
• Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis.
• Examines biometrics security-assisted applications and their integration using explainable AI.
The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.
Contents
1. Exploring Explainable AI: Techniques and Comparative Analysis. 2. Introduction to Explainable Artificial Intelligence in Biomedical and Healthcare Applications. 3. Smart Healthcare System: Automated Methods for diagnosis of diseases using Digital Twin Technology. 4. Explainable AI unlocks the Potential of AI in Biomedical Research and Practice. 5. An Intuitive Ensemble modelling with X-AI architecture for Autism classification. 6. Mental Disorder Management Using Explainable Artificial Intelligence. 7. Unlocking Insights: Data Analysis and Processing Empowered by Explainable AI. 8. Revolutionizing Healthcare: The Role of Artificial Intelligence in Transforming eHealth care. 9. Mental Disorders Management Using Explainable Artificial Intelligence (XAI). 10. Machine Learning Approach to Predict Adverse Effects of mRNA Vaccination: A Comparative Study of Classification Models and Ensemble Learning Techniques. 11. Explainable Artificial Intelligence (EAI): For Health Care Applications and Improvements. 12. Challenges and Imperatives for Equitable and Ethical Development of Explainable AI in Healthcare. 13. A Comprehensive Analysis of the Convergence Between Deep Learning Technologies and Bioinformatics, Catalyzing Groundbreaking Innovations in Biological Data Interpretation. 14. An Exhaustive Exploration of Explainable AI-Driven Applications in Healthcare, Enhancing Diagnostic Accuracy, Treatment Efficacy, and Patient Trust. 15. An In-Depth Exploration of Data Analysis and Processing Through the Prism of Explainable Artificial Intelligence Paradigms. 16. Implications of Artificial Intelligence in Disease Diagnosis
