Federated Learning in Metaverse Healthcare: Personalized Medicine and Wellness

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· Academic Press
eBook
300
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eBook 정보

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. - Explains privacy-preserving techniques in federated learning, such as federated averaging, differential privacy, and secure aggregation, thus ensuring the protection of sensitive healthcare data - Presents use cases and case studies that demonstrate the practical applications of federated learning in virtual healthcare settings - Illustrates its impact on patient care, medical research, and healthcare innovation - Contains contributions from leading experts in the fields of healthcare, artificial intelligence, and virtual reality, providing valuable insights and perspectives on the intersection of federated learning and metaverse healthcare

저자 정보

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.

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