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Federated Learning

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Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine.

Transfusion 39610333
BACKGROUND: Health data comprise data from different aspects of healthcare including administrative, digital health, and research-oriented data. Together, health data contribute to and inform healthcare operations, patient care, and research. Integra...
Artificial Intelligence Blood Transfusion Federated Learning Humans Information Dissemination Precision Medicine Privacy Transfusion Medicine
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DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum.

Neural networks : the official journal of the International Neural Network Society 39746248
To tackle high communication costs and privacy issues in Centralized Federated Learning (CFL), Decentralized Federated Learning (DFL) is an alternative. However, a significant discrepancy exists between local updates and the expected global update, k...
Algorithms Federated Learning Humans Machine Learning Neural Networks, Computer
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FedMEKT: Distillation-based embedding knowledge transfer for multimodal federated learning.

Neural networks : the official journal of the International Neural Network Society 39689572
Federated learning (FL) enables a decentralized machine learning paradigm for multiple clients to collaboratively train a generalized global model without sharing their private data. Most existing works have focused on designing FL systems for unimod...
Federated Learning Humans Machine Learning Neural Networks, Computer
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Federated learning for enhanced dose-volume parameter prediction with decentralized data.

Medical physics 39641909
BACKGROUND: The widespread adoption of knowledge-based planning in radiation oncology clinics is hindered by the lack of data and the difficulty associated with sharing medical data.
Federated Learning Humans Machine Learning Male Prostatic Neoplasms Radiation Dosage Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted
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Personalized federated learning for abdominal multi-organ segmentation based on frequency domain aggregation.

Journal of applied clinical medical physics 39636019
PURPOSE: The training of deep learning (DL) models in medical images requires large amounts of sensitive patient data. However, acquiring adequately labeled datasets is challenging because of the heavy workload of manual annotations and the stringent...
Abdomen Algorithms Deep Learning Federated Learning Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Tomography, X-Ray Computed
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Federated learning with bilateral defense via blockchain.

Neural networks : the official journal of the International Neural Network Society 39892356
Federated Learning (FL) offers benefits in protecting client data privacy but also faces multiple security challenges, such as privacy breaches from unencrypted data transmission and poisoning attacks that compromise model performance, however, most ...
Algorithms Blockchain Computer Security Federated Learning Humans Machine Learning
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Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images.

Scientific reports 39885198
The most common carcinoma-related cause of death among women is breast cancer. Early detection is crucial, and the manual screening method may lead to a delayed diagnosis, which would delay treatment and put lives at risk. Mammography imaging is advi...
Algorithms Breast Neoplasms Early Detection of Cancer Federated Learning Female Humans Machine Learning Mammography
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Out-of-Distribution Detection via outlier exposure in federated learning.

Neural networks : the official journal of the International Neural Network Society 39837184
Among various out-of-distribution (OOD) detection methods in neural networks, outlier exposure (OE) using auxiliary data has shown to achieve practical performance. However, existing OE methods are typically assumed to run in a centralized manner, an...
Algorithms Federated Learning Humans Machine Learning Neural Networks, Computer
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Federated learning meets Bayesian neural network: Robust and uncertainty-aware distributed variational inference.

Neural networks : the official journal of the International Neural Network Society 39826389
Federated Learning (FL) is a popular framework for data privacy protection in distributed machine learning. However, current FL faces some several problems and challenges, including the limited amount of client data and data heterogeneity. These lead...
Algorithms Bayes Theorem Federated Learning Humans Machine Learning Neural Networks, Computer Uncertainty
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FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.

Current medical imaging 39757652
BACKGROUND: Pneumonia is an acute respiratory infection that has emerged as the predominant catalyst for escalating mortality rates worldwide. In the pursuit of the prevention and prediction of pneumonia, this work employs the development of an advan...
Datasets as Topic Deep Learning Diagnosis, Computer-Assisted Federated Learning Humans Pneumonia
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