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Generation of Synthetic Data for the German Cancer Registries
Jean-Baptiste Escudié1,2, Karsten Berg2, Stefan Meisegeier2
1Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute.
Abstract:
This study presents quality evaluation methods and results of 4 major categories of machine learning models for the generation of synthetic data. On a 1 million samples subset of the historical German cancer registries data, all models could recover the distribution of the original data with large coverage and low invented relationships. The diffusion model resulted in the overall best metrics.
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