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Metaverse and AI in Healthcare

A Federated Learning Approach

  • 1st Edition - April 10, 2026
  • Latest edition
  • Editors: Jyotir Moy Chatterjee, Shubham Mahajan
  • Language: English

Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. The bo… Read more

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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.

Key features

  • 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

Readership

Graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare

Table of contents

Part 1: AI and Federated Learning Foundations in Healthcare

1. Introduction to the Convergence of Metaverse, AI, and Federated Learning in Healthcare

2. Exploring the Potential of Deep Learning for Transcription Factor Binding in Deoxyribose Nucleic Acid

3. Predictive Modeling of Alzheimer's Disease using MRI Images & Machine Learning Algorithms

4. Heart Disease Prediction using RBA: A Weighted Rivalry-Based Ensemble Learning Approach

5. Federated Learning and Machine Learning for the Detection of Heart Diseases

6. Predictive Modelling for Disease Prevention

7. A Resilient Federated Learning-Based Cybersecurity Framework for Healthcare Systems
Part 2: Metaverse and Augmented Reality in Healthcare

8. ARFIT: Redefining Fitness through Immersive Augmented Reality Experiences

9. Metasports in the Metaverse Era: A New Frontier for Athlete Performance and Health

10. Augmented Reality for Pediatric Rehabilitation: Legal Considerations for Disabled Children in India

11. Metaverse-Enabled Digital Twins: Building Intelligent and Ethical Healthcare Systems
Part 3: Legal, Ethical, and Cybersecurity Challenges

12. A Critical Evaluation of Blockchain Integration in Smart Healthcare System

13. Legal Perspectives on Cybersecurity for Digital Health Platforms Serving Disabled Children in India

14. Mitigating Bias in AI-Driven Burnout Risk Predictions for Optimal Staff Scheduling in Healthcare
Part 4: Strategic and Emerging Trends

15. Improving Cardiac MRI Analysis through Real-time Object Detection with YOLOv8

16. Digital Twin-Driven Cancer Survival Prediction: Machine Learning and EHR Integration for Smart Hospitals

17. ChatGPT in Medicine: Partnering with Doctors for Better Healthcare

18. Artificial Intelligence Based Medical Tourism in 2024 and Beyond: Emerging Trends, Challenges, and Strategic Imperatives

Product details

  • Edition: 1
  • Latest edition
  • Published: May 1, 2026
  • Language: English

About the editors

JM

Jyotir Moy Chatterjee

Jyotir Moy Chatterjee is currently an Assistant Professor in Department of Computer Science and Engineering at Graphic Era (Deemed to be University), in Dehradun, India. He also serves as a Visiting Faculty member in Information Technology at Lord Buddha Education Foundation, which is affiliated with the Asia Pacific University of Technology & Innovation in Kathmandu, Nepal. His research interests focus on advancements in Machine Learning and Deep Learning.

Affiliations and expertise
Assistant Professor, Department of CSE, Graphic Era University, Dehradun, India

SM

Shubham Mahajan

Dr. Shubham Mahajan is an academic and researcher, member of IEEE, ACM, and IAENG. He earned a B.Tech from Baba Ghulam Shah Badshah University, an M.Tech from Chandigarh University, and a PhD from Shri Mata Vaishno Devi University. He is currently Assistant Professor at Amity University, Haryana. His research spans artificial intelligence and image processing, including video compression, image segmentation, fuzzy entropy, nature-inspired optimization, data mining, machine learning, robotics, and optical communications. He holds patents internationally and has published widely in high-impact venues; he has edited several Scopus-indexed books. He has received multiple awards for research excellence and travel support from IEEE, among others. He has served as IEEE Campus Ambassador at premier institutes and promotes international collaborations. He participates in technical program committees and editorial boards for conferences and journals, shaping discourse in AI and image processing.

Affiliations and expertise
Amity School of Engineering and Technology, Amity University Haryana., India

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