The study compares seven synthetic data generators on four health datasets and proposes a visualization-aligned method to assess fidelity of joint distributions while noting medical domain adherence challenges.
3765067 Hernandez, M., Osorio-Marulanda, P
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Evaluating quality in synthetic data generation for large tabular health datasets
The study compares seven synthetic data generators on four health datasets and proposes a visualization-aligned method to assess fidelity of joint distributions while noting medical domain adherence challenges.