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Federated Learning in Metaverse Healthcare: Personalized Medicine and Wellness explores the integration of the metaverse with healthcare, offering immersive experiences and personalized care. The book introduces federated learning, emphasizing its advantages over traditional centralized machine learning in healthcare. It provides a historical context and discusses the technological advancements that led to the emergence of metaverse healthcare. Privacy-preserving methods crucial for protecting sensitive healthcare data within federated learning environments are also examined, underscoring the importance of secure communication protocols. Other important points include the transformation of healthcare delivery through virtual environments, remote consultations, and immersive experiences.
The role of telemedicine in facilitating remote diagnostics and consultations via virtual platforms, and the applications of augmented reality wearables for real-time health monitoring and wellness tracking are detailed. Additionally, the book discusses federated learning's ability to deliver personalized treatment plans tailored to individual patient needs, its role in predictive modeling for disease risks and prevention, as well as virtual health coaches offering personalized guidance for wellness management. The challenges and ethical dilemmas of metaverse healthcare and federated learning, along with potential solutions, are also considered.
Sommario
- Virtual Clinics and Hospitals: Transforming Healthcare in the Digital Age
- Navigating the Virtual Frontier: Challenges and Solutions for Ethical Federated Learning in Metaverse Healthcare in India
- Review of Deep Reinforcement Learning and Artificial Neural Networks in Healthcare Metaverse
- Virtual Clinical and Hospital in India
- Introduction to Metaverse Healthcare
- Telemedicine in the Metaverse
- Virtual Clinics and Healthcare Ecosystem
- A Collaborative Federated Learning Approach for Healthcare Informatics: Solutions & Challenges
- Privacy and Profit: The Dual Benefits of Federated Learning in Metaverse Healthcare Systems
- The Metaverse Shift: Adapting to Decentralized Computing in Federated Learning for Healthcare
- Federated Learning for Predictive Modeling of Disease Prevention in the Metaverse
- Integrating Real-Time Data with Predictive Models for Early Disease Detection in Metaverse Healthcare
- Augmented Reality Wearables for Health Monitoring in the Metaverse: Enhancing Patient Engagement and Clinical Outcomes
- Adapting to Decentralization: The Evolution of Computing Paradigms and Machine Learning in Federated Learning
- Privacy-Preserving Secure Computation: Bridging Traditional Healthcare and Metaverse Telemedicine
- Breaking the Boundaries: Optimizing Healthcare in the Metaverse through Federated Learning
Info autore
Shubham Mahajan is a distinguished academic and professional member of prestigious organizations such as IEEE, ACM, and IAENG. He specializes in artificial intelligence and image processing, holding eighteen Indian patents along with one each from Australia and Germany. His contributions to the field are further evidenced by his publications, which includes over 94 articles published in peer-reviewed journals and conferences and 10 edited books.
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.
