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Found 4 papers, 4 papers with code
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
Deploying federated learning (FL) in real-world scenarios, particularly in healthcare, poses challenges in communication and security.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, to software programming, networking, and security.
Privacy Preserving Image Registration
Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame.
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Affine Image Registration
Cubic splines Image Registration
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Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays Image
Over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19.
