Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task

@article{Wei2016AssessingTS,
  title={Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task},
  author={Chih-Hsuan Wei and Yifan Peng and Robert Leaman and Allan Peter Davis and Carolyn J. Mattingly and Jiao Li and Thomas C. Wiegers and Zhiyong Lu},
  journal={Database : the journal of biological databases and curation},
  year={2016},
  volume={2016}
}
Manually curating chemicals, diseases and their relationships is significantly important to biomedical research, but it is plagued by its high cost and the rapid growth of the biomedical literature. In recent years, there has been a growing interest in developing computational approaches for automatic chemical-disease relation (CDR) extraction. Despite these attempts, the lack of a comprehensive benchmarking dataset has limited the comparison of different techniques in order to assess and… CONTINUE READING
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Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature

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