AIMC Topic: Federated Learning

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Federated Learning for Predictive Analytics in Weaning from Mechanical Ventilation.

Studies in health technology and informatics May 15, 2025
Mechanical ventilation is crucial for critically ill patients in ICUs, requiring accurate weaning and extubations timing for optimal outcomes. Current prediction models struggle with generalizability across datasets like MIMIC-IV and eICU-CRD. We pro...
Humans Ventilator Weaning Federated Learning Respiration, Artificial Germany Machine Learning Intensive Care Units
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Enhancing Trust by a Keycloak-Flower Integration for Federated Machine Learning.

Studies in health technology and informatics May 15, 2025
Since its introduction, federated learning (FL) has attracted a lot of attention in the medical field, but its actual application in healthcare organisations remains limited. Flower is a leading FL framework known for its good documentation and wide ...
Systems Integration Federated Learning Machine Learning Trust Software Computer Security
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A Federated Learning Model for the Prediction of Blood Transfusion in Intensive Care Units.

Studies in health technology and informatics May 15, 2025
Accurate prediction of blood transfusion requirements is crucial for patient outcomes and resource management in clinical settings. We developed a machine learning model using XGBoost to predict the need for a blood transfusion 2 hours in advance bas...
Intensive Care Units Blood Transfusion Federated Learning Humans Machine Learning
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Federated Learning for Healthcare: Class Imbalance Mitigation and Feature Drift Detection.

Studies in health technology and informatics Apr 24, 2025
Federated learning (FL) has the potential to revolutionize healthcare by enabling collaborative data analysis while keeping data decentralized. Monitoring data quality is crucial for successful FL in healthcare, as undetected issues can compromise mo...
Humans Federated Learning Machine Learning Data Accuracy
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FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.

Current medical imaging Jan 1, 2025
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...
Federated Learning Pneumonia Datasets as Topic Humans Diagnosis, Computer-Assisted Deep Learning
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Cough Classification of Unknown Emerging Respiratory Disease with Federated Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Artificial intelligence offers great potential to address the need for rapid diagnostic testing in pandemic scenarios. Concerns about security and privacy, however, complicate the collection of large representative medical data. Federated Learning (F...
Federated Learning COVID-19 Algorithms SARS-CoV-2 Cough Machine Learning Humans Pandemics Artificial Intelligence
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Assessing the Impact of Federated Learning and Differential Privacy on Multi-centre Polyp Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Federated Learning (FL) is emerging in the medical field to address the need for diverse datasets while complying with data protection regulations. This decentralised learning paradigm allows hospitals (clients) to train machine learning models local...
Federated Learning Machine Learning Computer Security Image Processing, Computer-Assisted Humans Polyps Algorithms Privacy
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Towards Case-based Interpretability for Medical Federated Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
We explore deep generative models to generate case-based explanations in a medical federated learning setting. Explaining AI model decisions through case-based interpretability is paramount to increasing trust and allowing widespread adoption of AI i...
Pleural Effusion Federated Learning Artificial Intelligence Machine Learning Humans
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FedAssist: Federated Learning in AI-Powered Prosthetics for Sustainable and Collaborative Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
This paper explores the integration of federated learning in developing deep learning-powered surface electromyography decoding methods for AI-controlled prosthetics. Our proposed FL framework, FedAssist, aims to preserve data ownership while fosteri...
Humans Machine Learning Federated Learning Prostheses and Implants Algorithms Electromyography Deep Learning
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Federated Learning for Enhanced ECG Signal Classification with Privacy Awareness.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
This paper presents a novel approach for classifying electrocardiogram (ECG) signals in healthcare applications using federated learning and stacked convolutional neural networks (CNNs). Our innovative technique leverages the distributed nature of fe...
Federated Learning Signal Processing, Computer-Assisted Privacy Algorithms Electrocardiography Humans Neural Networks, Computer Machine Learning
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