Metaverse and AI in Healthcare
A Federated Learning Approach
- 1st Edition - May 1, 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 healthcar… Read more
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"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.
• 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
• 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
Graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare.
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
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
- Edition: 1
- Latest edition
- Published: May 1, 2026
- Language: English
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, IndiaSM
Shubham Mahajan
Dr. Shubham Mahajan, a distinguished member of prestigious organizations such as IEEE, ACM, and IAENG, boasts an impressive academic and professional background. He earned his B.Tech. degree from Baba Ghulam Shah Badshah University, his M.Tech. degree from Chandigarh University, and his Ph.D. degree from Shri Mata Vaishno Devi University (SMVDU) in Katra, India.
Dr. Mahajan has a remarkable track record in the field of artificial intelligence and image processing, holding an impressive portfolio of eleven Indian patents, as well as one Australian and one German patent. His contributions to the field are further evidenced by his extensive publication record, which includes over 100+ articles published in peer-reviewed journals, conferences and 10+ books. His research interests span a wide array of topics, encompassing image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. Notably, his dedication and expertise have earned him the 'Best Research Paper Award' from ICRIC 2019, published by Springer in the LNEE series.
In recognition of his exceptional achievements, Dr. Mahajan has received numerous accolades and honours throughout his career. These include the Best Student Award in 2019, the IEEE Region-10 Travel Grant Award in 2019, the 2nd runner-up prize in the IEEE RAS HACKATHON in 2019 (held in Bangladesh), the IEEE Student Early Researcher Conference Fund (SERCF) in 2020, the Emerging Scientist Award in 2021, and the IEEE Signal Processing Society Professional Development Grant in 2021. His commitment to excellence in research was further underscored by his receipt of the Excellence in Research Award in 2023.
Dr. Mahajan's impact extends beyond the realm of academia. He has served as a Campus Ambassador for IEEE, representing esteemed institutions such as IIT Bombay, Kanpur, Varanasi, Delhi, as well as various multinational corporations. His active engagement in fostering international research collaborations reflects his enthusiasm for advancing the frontiers of knowledge and innovation on a global scale.
Affiliations and expertise
Amity School of Engineering and Technology, Amity University Haryana., India