A reliable and privacy-preserved federated learning framework for real-time smoking prediction in healthcare
The ever-evolving domain of machine learning has witnessed significant advancements with the advent of federated learning, a paradigm revered for its capacity to facilitate model training on decentralized data sources while upholding data confidentiality. This research introduces a federated learnin...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Computer Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2024.1494174/full |
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