Validating GAN-BioBERT: A Methodology for Assessing Reporting Trends in Clinical Trials

@article{Myszewski2021ValidatingGA,
  title={Validating GAN-BioBERT: A Methodology for Assessing Reporting Trends in Clinical Trials},
  author={Joshua J. Myszewski and Emily Klossowski and Patrick Meyer and Kristin M Bevil and L Klesius and Kristopher M. Schroeder},
  journal={Frontiers in Digital Health},
  year={2021},
  volume={4}
}
Background The aim of this study was to validate a three-class sentiment classification model for clinical trial abstracts combining adversarial learning and the BioBERT language processing model as a tool to assess trends in biomedical literature in a clearly reproducible manner. We then assessed the model's performance for this application and compared it to previous models used for this task. Methods Using 108 expert-annotated clinical trial abstracts and 2,000 unlabeled abstracts this study… 
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