… enabling privacy-preserving and scalable healthcare applications. In this context, the
emerging concept of federated learning (FL) has shown promising solutions for providing privacy …

… sends the alert to the smart system, health alert transfer to the … prescribes the medicine to
the patient with some functions, … the privacy-preserving by blockchain and federated learning …

… existing privacy protection algorithms. Although there are various definitions of privacy in
federated learning, … Global privacy requires that the model's updates in each training round are …

… This article focuses on privacy leakage challenges and privacy protection technologies
from … The federated learning technology effectively protects medical and health data privacy …

… Federated learning (FL) allows for multi-institutional training of AI models, obviating data
sharing, albeit with different security and privacy … We thus summarize privacy-preserving FL …

… of the most advanced privacy preserved MIoT systems based on federal learning. …
privacy-preserving and federated machine learning in medical imaging,” Nature Machine Intelligence…

… a federated learning framework that can learn a global model from distributed health data held
locally at different sites. The framework offers two levels of privacy … model training process. …

… training and learning process and get the desired result. In Fig. 2 the framework of Federated
learning for preserving privacy … repeated by the server to coordinate the training process: …

… privacy-preserving federated learning models is fundamentally anchored on the quality and
applicability of the training … two datasets: the Medical Information Mart for Intensive Care III (…

… The purpose of this work is to study the performance of federated learning algorithm in
privacy preserving machine learning applications. Particularly in this work, we focus on facial …