Comprehensive evaluation framework for synthetic tabular data in health: fidelity, utility and privacy analysis of generative models with and without privacy guarantees
The generation of synthetic tabular data has emerged as a key privacy-enhancing technology to address challenges in data sharing, particularly in healthcare, where sensitive attributes can compromise patient privacy. Despite significant progress, balancing fidelity, utility, and privacy in complex m...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Digital Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1576290/full |
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