Synthesizing electronic health records using improved generative adversarial networks.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Mar 1, 2019

Abstract

OBJECTIVE: The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method.

Authors

  • Mrinal Kanti Baowaly
    Social Networks and Human-Centered Computing, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, Taiwan.
  • Chia-Ching Lin
    Graduate Institute of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
  • Chao-Lin Liu
    Department of Computer Science, National Chengchi University, Taipei, Taiwan.
  • Kuan-Ta Chen
    Institute of Information Science, Academia Sinica, Taipei, Taiwan.

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