Systematic review of 134 studies consolidates synthetic tabular health data evaluation methods into taxonomies and provides guidelines to address challenges like inconsistent metrics and limited reproducibility.
A joint learning method for incomplete and imbalanced data in electronic health record based on generative adversarial networks.Computers in Biology and Medicine, 168:107687
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Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review
Systematic review of 134 studies consolidates synthetic tabular health data evaluation methods into taxonomies and provides guidelines to address challenges like inconsistent metrics and limited reproducibility.