Nature Communications (Dec 2022)

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

DOI
https://doi.org/10.1038/s41467-022-35295-1
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 18

Abstract

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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.