Using Artificial Intelligence to Generate Synthetic Health Data

Federico Girosi, Sai Prathyush Katragadda, Joshua Steier, Raffaele Vardavas

Published Oct 3, 2023

Generating synthetic data enables making sensitive data sets available to the research community. This report utilizes two off-the-shelf methods to generate synthetic health data. One method, synthpop, is based on standard statistical techniques. The other, CTGAN, is a deep learning generative adversarial network. The authors compare the performance of the methods and discuss the reasons for which synthpop outperforms CTGAN on these data.

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Girosi, Federico, Sai Prathyush Katragadda, Joshua Steier, and Raffaele Vardavas, Using Artificial Intelligence to Generate Synthetic Health Data. Santa Monica, CA: RAND Corporation, 2023. https://www.rand.org/pubs/working_papers/WRA2892-1.html.
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