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Validating a membership disclosure metric for synthetic health data
BACKGROUND: One of the increasingly accepted methods to evaluate the privacy of synthetic data is by measuring the risk of membership disclosure. This is a measure of the F1 accuracy that an adversary would correctly ascertain that a target individual from the same population as the real data is in...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553223/ https://www.ncbi.nlm.nih.gov/pubmed/36238080 http://dx.doi.org/10.1093/jamiaopen/ooac083 |