Corpus ID: 9839235

Overview of the CHEMDNER patents task

@inproceedings{Krallinger2015OverviewOT,
  title={Overview of the CHEMDNER patents task},
  author={Martin Krallinger and O. Rabal and A. Lourenço and M. P{\'e}rez and Gael P{\'e}rez Rodr{\'i}guez and M. Vazquez and F. Leitner and J. Oyarz{\'a}bal and A. Valencia},
  year={2015}
}
A considerable effort has been made to extract biological and chemical entities, as well as their relationships, from the scientific literature, either manually through traditional literature curation or by using information extraction and text mining technologies. Medicinal chemistry patents contain a wealth of information, for instance to uncover potential biomarkers that might play a role in cancer treatment and prognosis. However, current biomedical annotation databases do not cover such… Expand

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