Metaverse and AI in Healthcare
A Federated Learning Approach
Published on 10. April 2026
400 pages
978-0-443-44959-8 (ISBN)
Description
Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. The book fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends.Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism which are supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis.
- Explores cutting-edge AI and federated learning applications in healthcare
- Provides practical guidance on privacy and cybersecurity in digital health
- Integrates emerging metaverse and augmented reality technologies
- Presents multidisciplinary perspectives with diverse expert contributors
- Includes real-world case studies and future trends in healthcare innovation
More details
Other editions
Additional editions
Book
approx. 05/2026
Academic Press
€184.50
Not yet published
Content
Part 1: AI and Federated Learning Foundations in Healthcare1. Introduction to the Convergence of Metaverse, AI, and Federated Learning in Healthcare2. Exploring the Potential of Deep Learning for Transcription Factor Binding in Deoxyribose Nucleic Acid3. Predictive Modeling of Alzheimer's Disease using MRI Images & Machine Learning Algorithms4. Heart Disease Prediction using RBA: A Weighted Rivalry-Based Ensemble Learning Approach5. Federated Learning and Machine Learning for the Detection of Heart Diseases6. Predictive Modelling for Disease Prevention7. A Resilient Federated Learning-Based Cybersecurity Framework for Healthcare SystemsPart 2: Metaverse and Augmented Reality in Healthcare8. ARFIT: Redefining Fitness through Immersive Augmented Reality Experiences9. Metasports in the Metaverse Era: A New Frontier for Athlete Performance and Health10. Augmented Reality for Pediatric Rehabilitation: Legal Considerations for Disabled Children in India11. Metaverse-Enabled Digital Twins: Building Intelligent and Ethical Healthcare SystemsPart 3: Legal, Ethical, and Cybersecurity Challenges12. A Critical Evaluation of Blockchain Integration in Smart Healthcare System13. Legal Perspectives on Cybersecurity for Digital Health Platforms Serving Disabled Children in India14. Mitigating Bias in AI-Driven Burnout Risk Predictions for Optimal Staff Scheduling in HealthcarePart 4: Strategic and Emerging Trends15. Improving Cardiac MRI Analysis through Real-time Object Detection with YOLOv816. Digital Twin-Driven Cancer Survival Prediction: Machine Learning and EHR Integration for Smart Hospitals17. ChatGPT in Medicine: Partnering with Doctors for Better Healthcare18. Artificial Intelligence Based Medical Tourism in 2024 and Beyond: Emerging Trends, Challenges, and Strategic Imperatives
