Towards fairness-aware and privacy-preserving enhanced collaborative learning for healthcare
Abstract The widespread integration of AI algorithms in healthcare has sparked ethical concerns, particularly regarding privacy and fairness. Federated Learning (FL) offers a promising solution to learn from a broad spectrum of patient data without directly accessing individual records, enhancing pr...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58055-3 |
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