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Generation and Evaluation of Synthetic Data in a University Hospital Setting
Bayrem Kaabachi1,2, Jérémie Despraz1, Thierry Meurers3
1Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.
Abstract:
In this study, we propose a unified evaluation framework for systematically assessing the utility-privacy trade-off of synthetic data generation (SDG) models. These SDG models are adapted to deal with longitudinal or tabular data stemming from electronic health records (EHR) containing both discrete and numeric features. Our evaluation framework considers different data sharing scenarios and attacker models.
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