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Asynchronous and Flexible Federated Learning for COVID-19 Detection from Chest X-Ray Images

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This approach demonstrates a decentralized model for COVID-19 screening using chest X-rays, suggesting enhanced privacy and scalability.

The novel federated learning framework enables secure COVID-19 detection from chest X-ray images.
By using asynchronous communication, the system effectively addresses delays due to device heterogeneity.
This method achieves performance comparable to centralized systems while preserving data privacy.
The framework's support for heterogeneous client models enhances local training efficiencies.

Elhajjej et al. (2025) studied this question.

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