Full Description
Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. It 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, 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. It empowers readers to navigate evolving digital health ecosystems, addressing data privacy, customized care, and global access challenges through federated learning and metaverse solutions.
Contents
Section 1: Foundational Concepts & Emerging Trends
1. Introduction to the Convergence of Metaverse, AI, and Federated Learning in Healthcare
2. ChatGPT in Medicine: Partnering with Doctors for Better Healthcare
3. Artificial Intelligence-based Medical Tourism in 2024 and Beyond: Emerging Trends, Challenges, and Strategic Imperatives
4. ARFIT: Redefining Fitness through Immersive Augmented Reality Experiences
5. Augmented Reality for Pediatric Rehabilitation: Legal Considerations for Disabled Children in India
6. Metasports in the Metaverse Era: A New Frontier for Athlete Performance and Health
7. Predictive Modelling for Disease Prevention
8. Bias in the Machine: Ethical Challenges and Solutions in AI Development
Section 2: Applied AI & ML in Smart Healthcare
9. Predictive Modeling of Alzheimer's Disease using MRI Images & Machine Learning Algorithms
10. Heart Disease Prediction using RBA: A Weighted Rivalry-Based Ensemble Learning Approach
11. Improving Cardiac MRI Analysis through Real-time Object Detection with YOLOv8
12. A Critical Evaluation of Blockchain Integration in Smart Healthcare System
13. Federated Learning and Machine Learning for the Detection of Heart Diseases
14. Revolutionizing Patient Care with Digital Twins: A Smart Healthcare Perspective
Section 3: Cutting-edge Research & Strategic Systems
15. A Resilient Federated Learning-Based Cybersecurity Framework for Healthcare Systems
16.Exploring the Potential of Deep Learning for Transcription Factor Binding in Deoxyribose Nucleic Acid
17. Navigating the Pulse in Industry 6.0: Assessing the Resilience of India's Healthcare Grid
