A systematic review of federated learning: Challenges, aggregation methods, and development tools
BS Guendouzi, S Ouchani, HEL Assaad… - Journal of Network and …, 2023 - Elsevier
Since its inception in 2016, federated learning has evolved into a highly promising decentral-
ized machine learning approach, facilitating collaborative model training across numerous …
ized machine learning approach, facilitating collaborative model training across numerous …
A reinforcement federated learning based strategy for urinary disease dataset processing
Urinary disease is a complex healthcare issue that continues to grow in prevalence. Urine
tests have proven valuable in identifying conditions such as kidney disease, urinary tract …
tests have proven valuable in identifying conditions such as kidney disease, urinary tract …
Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity
Z Zhang, L Chen, X Liu, J Yang, J Huang, Q Yang… - Intensive Care …, 2023 - Springer
Purpose Various studies have analyzed sepsis subtypes, yet the reproducibility of such
results remains unclear. This study aimed to determine the reproducibility of sepsis subtypes …
results remains unclear. This study aimed to determine the reproducibility of sepsis subtypes …
Yoga: Adaptive layer-wise model aggregation for decentralized federated learning
Traditional Federated Learning (FL) is a promising paradigm that enables massive edge
clients to collaboratively train deep neural network (DNN) models without exposing raw data …
clients to collaboratively train deep neural network (DNN) models without exposing raw data …
[HTML][HTML] Federated systems for automated infection surveillance: a perspective
SM van Rooden… - Antimicrobial …, 2024 - aricjournal.biomedcentral.com
Automation of surveillance of infectious diseases—where algorithms are applied to routine
care data to replace manual decisions—likely reduces workload and improves quality of …
care data to replace manual decisions—likely reduces workload and improves quality of …
EHR privacy preservation using federated learning with DQRE-Scnet for healthcare application domains
A distributed learning technique named Federated Learning (FL) is utilized by mobile
devices, clinical research labs, and hospitals for secure healthcare data sharing. FL has …
devices, clinical research labs, and hospitals for secure healthcare data sharing. FL has …
An adaptive federated learning framework for clinical risk prediction with electronic health records from multiple hospitals
Clinical risk prediction with electronic health records (EHR) using machine learning has
attracted lots of attentions in recent years, where one of the key challenges is how to protect …
attracted lots of attentions in recent years, where one of the key challenges is how to protect …
Federated learning-based prediction of depression among adolescents across multiple districts in China
Depression in adolescents is a serious mental health condition that can affect their
emotional and social well-being. Detailed understanding of depression patterns and status …
emotional and social well-being. Detailed understanding of depression patterns and status …
EHRFL: Federated Learning Framework for Heterogeneous EHRs and Precision-guided Selection of Participating Clients
In this study, we provide solutions to two practical yet overlooked scenarios in federated
learning for electronic health records (EHRs): firstly, we introduce EHRFL, a framework that …
learning for electronic health records (EHRs): firstly, we introduce EHRFL, a framework that …
Empowering precise advertising with Fed-GANCC: A novel federated learning approach leveraging Generative Adversarial Networks and group clustering
C Su, J Wei, Y Lei, H Xuan, J Li - Plos one, 2024 - journals.plos.org
In the realm of targeted advertising, the demand for precision is paramount, and the
traditional centralized machine learning paradigm fails to address this necessity effectively …
traditional centralized machine learning paradigm fails to address this necessity effectively …