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Fold-stratified cross-validation for unbiased and privacy-preserving federated learning
OBJECTIVE: We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs). MATERIALS AND METHODS: Fold-stratified cross-validation complement...
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| Veröffentlicht in: | J Am Med Inform Assoc |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Oxford University Press
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7647321/ https://ncbi.nlm.nih.gov/pubmed/32620945 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocaa096 |
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