AIMC Topic: Federated Learning

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Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

Ophthalmology. Glaucoma Aug 29, 2024
CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical presentations, making diagnosis and management challenging. The lack of a consensus definition for glaucoma or glaucomatous optic neuropathy further compli...
Deep Learning Federated Learning Humans Artificial Intelligence Glaucoma Machine Learning
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Federated Learning for Renal Tumor Segmentation and Classification on Multi-Center MRI Dataset.

Journal of magnetic resonance imaging : JMRI Sep 1, 2025
BACKGROUND: Deep learning (DL) models for accurate renal tumor characterization may benefit from multi-center datasets for improved generalizability; however, data-sharing constraints necessitate privacy-preserving solutions like federated learning (...
Humans Algorithms Reproducibility of Results Aged Adult Retrospective Studies Female Kidney Federated Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Kidney Neoplasms Deep Learning Image Processing, Computer-Assisted Male Middle Aged
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FedPPD: Towards effective subgraph federated learning via pseudo prototype distillation.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2025
Subgraph federated learning (subgraph-FL) is a distributed machine learning paradigm enabling cross-client collaborative training of graph neural networks (GNNs). However, real-world subgraph-FL scenarios often face subgraph heterogeneity problem, i....
Algorithms Federated Learning Neural Networks, Computer Machine Learning
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Evaluation of Federated Learning Using Standardized EHR Data in Japan.

Studies in health technology and informatics Aug 7, 2025
This study addresses privacy concerns in multi-institutional data sharing by applying federated learning (FL) to develop a predictive model for prolonged air leaks (PAL) following video-assisted thoracoscopic surgery (VATS). Utilizing standardized el...
Machine Learning Japan Electronic Health Records Information Dissemination Humans Federated Learning Confidentiality Thoracic Surgery, Video-Assisted
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Self-attention fusion and adaptive continual updating for multimodal federated learning with heterogeneous data.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning (FL) enables collaborative model training without direct data sharing, facilitating knowledge exchange while ensuring data privacy. Multimodal federated learning (MFL) is particularly advantageous for decentralized multimodal data,...
Humans Neural Networks, Computer Machine Learning Federated Learning Algorithms Attention
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FedELR: When federated learning meets learning with noisy labels.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Existing research on federated learning (FL) usually assumes that training labels are of high quality for each client, which is impractical in many real-world scenarios (e.g., noisy labels by crowd-sourced annotations), leading to dramatic performanc...
Machine Learning Federated Learning Neural Networks, Computer Algorithms
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Learn the global prompt in the low-rank tensor space for heterogeneous federated learning.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning collaborates with multiple clients to train a global model, enhancing the model generalization while allowing the local data transmission-free and security. However, federated learning currently faces three intractable challenges: ...
Learning Federated Learning Machine Learning Algorithms Humans Neural Networks, Computer
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StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data samples are often decentralized and Non-Independently Identically Dist...
Humans Neural Networks, Computer Cluster Analysis Machine Learning Stochastic Processes Algorithms Federated Learning
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Quantum federated learning with pole-angle quantum local training and trainable measurement.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Recently, quantum federated learning (QFL) has received significant attention as an innovative paradigm. QFL has remarkable features by employing quantum neural networks (QNNs) instead of conventional neural networks owing to quantum supremacy. In or...
Federated Learning Algorithms Quantum Theory Neural Networks, Computer Machine Learning
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Federated Machine Learning Enables Risk Management and Privacy Protection in Water Quality.

Environmental science & technology Jun 3, 2025
Real-time water quality risk management in wastewater treatment plants (WWTPs) requires extensive data, and data sharing is still just a slogan due to data privacy issues. Here we show an adaptive water system federated averaging (AWSFA) framework ba...
Water Quality Federated Learning Machine Learning Wastewater Risk Management Privacy
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