Oct 4, 2021 · Comparing the performances of two recent distributed learning approaches - Federated Learning and Split Learning - on the task of Automated Chest X-Ray ...
Oct 4, 2021 · Our work aims to compare two distributed machine learning approaches, Split Learning and Federated Learning, in the context of Automated CXR ...
Distributed deep learning methods enable deep learning models to be trained without the need for sharing data from these centres while still preserving the ...
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May 2, 2024 · By automating the detection of abnormalities in chest X-rays, CNN-based models can expedite the diagnostic process, leading to earlier detection ...
1. Deep Learning model. The system is a combination of four convolutional neural networks, which detect four critical findings in chest x-rays. For triage ...
Sep 18, 2023 · Our research focused on creating an advanced machine-learning algorithm that accurately detects anomalies in chest X-ray images.
Feb 8, 2024 · This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radiograph ...
Aug 21, 2024 · A proposed artificial intelligence model based on supervised contrastive learning effectively minimized bias in automated chest radiograph diagnosis.
Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy.
In this study, we propose an approach of federated learning for classifying chest diseases from chest X-ray images employing the NIH Chest X-ray dataset.
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