The Convergence of Federated Learning and Healthcare 5.0 and Beyond: A New Era of Intelligent Health Systems
The Convergence of Federated Learning and Healthcare 5.0 and Beyond: ...
Contenu
This book introduces a novel integration of Federated Learning with the vision of Healthcare 5.0 to enable secure, adaptive, and intelligent health systems. It presents cutting-edge frameworks that support decentralized model training across medical institutions while preserving patient privacy and ensuring compliance with data regulations.
Focusing on real-world use cases, such as predictive diagnostics, edge-based patient monitoring, personalized medicine, and surgical robotics, it bridges theoretical advances with practical implementations. This book provides deep insights into the design of scalable, privacy-preserving artificial intelligence infrastructures suited for cross-institutional collaboration.
It is designed for artificial intelligence researchers, digital health architects, healthcare technologists, and policy advisors. This supports the development of human-centric, resilient, and interoperable smart healthcare ecosystems.
Informations bibliographiques
janvier 2026, Studies in Computational Intelligence, Anglais
Springer International Publishing
978-3-032-03984-2