Corpus ID: 236087310

Clinical Relation Extraction Using Transformer-based Models

@article{Yang2021ClinicalRE,
  title={Clinical Relation Extraction Using Transformer-based Models},
  author={Xi Yang and Zehao Yu and Yi Guo and Jiang Bian and Yonghui Wu},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.08957}
}
  • Xi Yang, Zehao Yu, +2 authors Yonghui Wu
  • Published 2021
  • Computer Science
  • ArXiv
The newly emerged transformer technology has a tremendous impact on NLP research. In the general English domain, transformer-based models have achieved state-of-the-art performances on various NLP benchmarks. In the clinical domain, researchers also have investigated transformer models for clinical applications. The goal of this study is to systematically explore three widely used transformer-based models (i.e., BERT, RoBERTa, and XLNet) for clinical relation extraction and develop an open… Expand
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