Resource-Aware Federated Hybrid Profiling for Edge Node Selection in Federated Patient Similarity Network
The widespread adoption of edge computing for resource-constrained devices presents
challenges in computational straggler issues, primarily due to the heterogeneity of edge …
challenges in computational straggler issues, primarily due to the heterogeneity of edge …
Empowering Patient Similarity Networks through Innovative Data-Quality-Aware Federated Profiling
Continuous monitoring of patients involves collecting and analyzing sensory data from a
multitude of sources. To overcome communication overhead, ensure data privacy and …
multitude of sources. To overcome communication overhead, ensure data privacy and …
Federated Patient Similarity Network for Data-Driven Diagnosis of COVID-19 Patients
Sensitive patient data is generated from a variety of sources and then transferred to a cloud
for processing. Therefore, it is exposed to security and privacy and may lead to an increase …
for processing. Therefore, it is exposed to security and privacy and may lead to an increase …
Fed xData: A federated learning framework for enabling contextual health monitoring in a cloud-edge network
Due to the rapid recent development of cloud-edge networks, smart devices can facilitate
rapid access to patients' health information. Success has been achieved in the healthcare …
rapid access to patients' health information. Success has been achieved in the healthcare …
Collaborative Estimating Multiple Gaussian Graphical Models on Resource Constrained Devices in IoT Networks
Y Zhan, B Wang - … on Systems, Man, and Cybernetics (SMC), 2023 - ieeexplore.ieee.org
In recent years, the rapid development of the Internet of Things (IoT) has attracted significant
interest in smart healthcare. However, such collaborative IoT applications still face three …
interest in smart healthcare. However, such collaborative IoT applications still face three …
Enhanced decision-making in healthcare cloud-edge networks using deep reinforcement and lion optimization algorithm
Addressing the limitations of traffic-centric approaches in cooperative cloud-edge networks,
this paper introduces an adaptive deployment strategy for FDNN using LOA. However, the …
this paper introduces an adaptive deployment strategy for FDNN using LOA. However, the …
Personalized-Enhanced Federated Learning on Heterogeneous Internet of Medical Things
Y Lv, L Yan, P Zhang, D Hu… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The significant heterogeneity of data resources in Internet of Medical Things (IoM T) devices
profoundly affects the efficacy of federated learning (FL) when training medical models …
profoundly affects the efficacy of federated learning (FL) when training medical models …
DRAGON: Decentralized fault tolerance in edge federations
Edge Federation is a new computing paradigm that seamlessly interconnects the resources
of multiple edge service providers. A key challenge in such systems is the deployment of …
of multiple edge service providers. A key challenge in such systems is the deployment of …
Random forest for data aggregation to monitor and predict COVID-19 using edge networks
Medical sensors and distributed edge networks hold promise in advanced control and
prediction of infectious diseases, such as COVID-19. Their integration can lower …
prediction of infectious diseases, such as COVID-19. Their integration can lower …
[PDF][PDF] Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling
Intelligent healthcare networks represent a significant component in digital applications,
where the requirements hold within quality-of-service (QoS) reliability and safeguarding …
where the requirements hold within quality-of-service (QoS) reliability and safeguarding …