Federated Learning in Metaverse Healthcare

Personalized Medicine and Wellness
Erscheinungsjahr 2025
ISBN: 978-0-443-33789-5
Verlag: Elsevier Science

Buch, Englisch, 300 Seiten, Format (B × H): 191 mm x 235 mm

Federated Learning in Metaverse Healthcare: Personalized Medicine and Wellness explores the integration of the metaverse with healthcare, offering immersive experiences and personalized care. It introduces federated learning, highlighting its advantages over centralized machine learning in healthcare. The historical context and technological advancements that have led to the emergence of metaverse healthcare are explored, along with privacy-preserving methods crucial for protecting sensitive healthcare data in federated learning environments. The transformation of healthcare delivery through virtual environments, remote consultations, and immersive experiences is discussed, as well as the role of telemedicine in facilitating remote diagnostics and consultations through virtual platforms. The applications of augmented reality wearables in real-time health monitoring and wellness tracking are explored. The architecture and components of federated learning systems within metaverse healthcare environments are detailed, emphasizing the importance of secure communication protocols in safeguarding healthcare data. Federated learning's ability to deliver personalized treatment plans tailored to individual patient needs, as well as its role in predictive modeling for disease risks and prevention strategies, is examined. Virtual health coaches leveraging federated learning algorithms to provide personalized guidance and support for wellness management are also discussed. The challenges and ethical dilemmas inherent in metaverse healthcare and federated learning are considered, along with potential solutions. Finally, the future of metaverse healthcare and federated learning is speculated, highlighting emerging trends and areas for further research and development.

Autoren/Hrsg.

Moy Chatterjee, Jyotir

Mahajan, Shubham

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe

Inhaltsverzeichnis

1. Virtual Clinics and Hospitals: Transforming Healthcare in the Digital Age
2. Navigating the Virtual Frontier: Challenges and Solutions for Ethical Federated Learning in Metaverse Healthcare in India
3. Review of Deep Reinforcement Learning and Artificial Neural Networks in Healthcare Metaverse
4. Virtual Clinical and Hospital In India
5. Introduction to Metaverse Healthcare
6. Telemedicine in Metaverse
7. Virtual Clinics and Healthcare Ecosystem
8. A collaborated federated learning for healthcare informatics: Solution & challenges
9. Privacy and Profit: The Dual Benefits of Federated Learning in Metaverse Healthcare Systems
10. The Metaverse Shift: Adapting to Decentralized Computing in Federated Learning for Healthcare
11. Federated Learning for Predictive Modelling of Disease Prevention in Metaverse
12. Integrating Real-Time Data with Predictive Models for Early Disease Detection in Metaverse Healthcare
13. Augmented Reality Wearables for Health Monitoring in the Metaverse: Enhancing Patient Engagement and Clinical Outcomes
14. Exploring the Potential of Deep Learning for Transcription Factor Binding in Deoxyribose Nucleic Acid
15. Adapting to Decentralization: The Evolution of Computing Paradigms and Machine Learning in Federated Learning
16. Privacy-Preserving Secure Computation: Bridging Traditional Healthcare and Metaverse Telemedicine
17. Breaking the Boundaries: Optimizing Healthcare in the Metaverse through Federated Learning
18. ChatGPT in Medicine: Partnering with Doctors for Better Healthcare
19. Federated Learning and Machine Learning for the Detection of Heart Diseases
20. ARFIT: Redefining Fitness through Immersive Augmented Reality Experiences
21. A critical evaluation of blockchain integration in smart healthcare system
22. Predictive Modeling of Alzheimer's Disease using MRI Images & Machine Learning Algorithms
23. Artificial Intelligence based Medical Tourism in 2024 and Beyond: Emerging Trends, Challenges, and Strategic Imperatives
24. Augmented Reality for Pediatric Rehabilitation: Legal Considerations for Disabled Children in India
25. Improving Cardiac MRI Analysis through Real-time Object Detection with YOLOv8
26. Legal Perspectives on Cybersecurity for Digital Health Platforms Serving Disabled Children in India
27. Metasports in the Metaverse Era: A New Frontier for Athlete Performance and Health
28. Heart Disease Prediction using RBA: A Weighted Rivalry-Based Ensemble Learning Approach
29. A Resilient Federated Learning-Based Cybersecurity Framework for Healthcare Systems
30. Predictive Modelling for Disease Prevention

Über Autor(innen)

Mahajan, Shubham
Dr. Shubham Mahajan is a distinguished academic and professional member of prestigious organizations such as IEEE, ACM, and IAENG. He earned his B.Tech. from Baba Ghulam Shah Badshah University, M.Tech. from Chandigarh University, Ph.D. from Shri Mata Vaishno Devi University in India and Post Doctoral degree in Applied Data Science at Noroff University College in Norway and Currently, he is working as an Assistant Professor at Amity University, Haranya, India.

Dr. Mahajan specializes in artificial intelligence and image processing, holding eleven Indian patents along with one each from Australia and Germany. His extensive publication record includes over 94 articles in peer-reviewed journals and conferences, covering topics such as image segmentation, data mining, and machine learning. He received the 'Best Research Paper Award' from ICRIC 2019, published in the Springer LNEE series.

Moy Chatterjee, Jyotir
Dr. 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.