A Multifaceted benchmarking of synthetic electronic health record generation models - Chao Yan; Yao Yan; Zhiyu Wan; Ziqi Zhang; Larsson Omberg; Justin Guinney; Sean D. Mooney; Bradley A. Malin (Nature Communications, 2022)
Synthetic health data have the potential to mitigate privacy concerns when sharing data to support biomedical research and the development of innovative healthcare applications. In this work, the authors introduce a use case oriented benchmarking framework to evaluate data synthesis models through a set of utility and privacy metrics.