… First, Section 3.1 explores the evolution of studies on federated learning applied to
healthcare, including the main research issues and proposed solutions. Next, Section 3.2 …

… federated learning in healthcare applications. Second, we evaluate a set of recent challenges
from a data-centric perspective in federated learning, … directions in healthcare applications. …

… that are useful to federated smart healthcare in Section 4. In … applications of FL in smart
healthcare, namely federated EHRs management, federated remote health monitoring, federated …

… In this review, after a formal overview of federated learning, we … the potential of federated
learning methods in healthcare by … and open questions for future applications in healthcare. …

… domain, this report discusses the opportunities and challenges in federated learning. …
federated learning can serve as an option for building a collaborative learning model for healthcare …

… These includes cases in health care or mobile devices that data are not available to be …
learning method to process federated training. FC API, the basic layer for federation learning, …

… , which is collected in huge volumes by modern healthcare systems. Existing medical data
is not … how federated learning (FL) may provide a solution for the future of digital health and …

… Federated learning deals … federated learning have been rigorously reviewed. This meta-analysis
provides an in-depth review of the federated learning architectures, federated learning …

… learning (ML) model, federated learning (… federated learning (FL) and its development. The
focus, especially in Sections 3.6 and 4, is laid on the usability of FL for healthcare and health-…

… federated learning systems, with a focus on healthcare. FL is reviewed in terms of its
frameworks, architectures and applications… with a shared global deep learning (DL) model via a …