A survey of generative adversarial networks for synthesizing structured electronic health records
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and point of care applications; however, many challenges such as data privacy concerns impede its optimal utilization. Deep generative models, particularly, Generative Adversarial Networks (GANs) show great promise...
Main Authors: | , , |
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Format: | Journal article |
Language: | English |
Published: |
Association for Computing Machinery
2024
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