Federated learning with non-iid data: A survey
Z Lu, H Pan, Y Dai, X Si, Y Zhang - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning (FL) is an efficient decentralized machine learning methodology for
processing nonindependent and identically distributed (non-IID) data due to geographical …
processing nonindependent and identically distributed (non-IID) data due to geographical …
Road network traffic flow prediction: A personalized federated learning method based on client reputation
Accurate traffic flow prediction can provide effective decision-making support for traffic
management, alleviate traffic congestion, and improve road traffic efficiency. Traffic flow data …
management, alleviate traffic congestion, and improve road traffic efficiency. Traffic flow data …
Explainable Deep Contrastive Federated Learning System for Early Prediction of Clinical Status in-Intensive Care Unit
Early identification of patients' clinical status plays a critical role in intensive care unit (ICU)
care. The increased adoption of electronic health records (EHRs) in the ICU creates …
care. The increased adoption of electronic health records (EHRs) in the ICU creates …
[HTML][HTML] Multicenter analysis of emergency patient severity through local model evaluation client selection: optimizing client selection based on local model evaluation
Y Kim, SM Yang, KY Lee - Applied Sciences, 2024 - mdpi.com
In multi-institutional emergency room settings, the early identification of high-risk patients is
crucial for effective severity management. This necessitates the development of advanced …
crucial for effective severity management. This necessitates the development of advanced …
Multicenter Knowledge Transfer Calibration with Rapid 0th-Order TSK Fuzzy System for Small Sample Epileptic EEG Signals
The diagnosis and treatment of epilepsy necessitate the precise identification and
classification of electroencephalogram (EEG) signals. However, EEG samples from different …
classification of electroencephalogram (EEG) signals. However, EEG samples from different …
FedICU: a federated learning model for reducing the medication prescription errors in intensive care units
Patients in the Intensive care unit need remarkable observation. This unit consists of people
who are critically ill and may tend to lose their lives anytime. Healthcare professionals in …
who are critically ill and may tend to lose their lives anytime. Healthcare professionals in …
FedGlu: A personalized federated learning-based glucose forecasting algorithm for improved performance in glycemic excursion regions
Continuous glucose monitoring (CGM) devices provide real-time glucose monitoring and
timely alerts for glycemic excursions, improving glycemic control among patients with …
timely alerts for glycemic excursions, improving glycemic control among patients with …
Combining Reverse Temporal Attention Mechanism and Dynamic Similarity Analysis for Disease Prediction
X Zhang, Y Lei, G Li, S Wang… - … , Intl Conf on Cloud and Big …, 2023 - ieeexplore.ieee.org
In recent years, the explosive growth of the Internet has made it an indispensable part of our
daily study, work and life. With the rapid development of the medical industry and …
daily study, work and life. With the rapid development of the medical industry and …
Federated Learning: Bridging Data Privacy and Model Accuracy on JointCloud
J Guo, B Yi, X Wang, J Zhang, E Lv, K Zhang… - … Conference on Intelligent …, 2024 - Springer
JointCloud is a novel collaborative cross-cloud architecture which is used to integrate and
manager services of multiple clouds. Federated learning brings a promising intelligent …
manager services of multiple clouds. Federated learning brings a promising intelligent …