Improving chemical disease relation extraction with rich features and weakly labeled data.

Journal: Journal of cheminformatics
Published Date: Oct 7, 2016

Abstract

BACKGROUND: Due to the importance of identifying relations between chemicals and diseases for new drug discovery and improving chemical safety, there has been a growing interest in developing automatic relation extraction systems for capturing these relations from the rich and rapid-growing biomedical literature. In this work we aim to build on current advances in named entity recognition and a recent BioCreative effort to further improve the state of the art in biomedical relation extraction, in particular for the chemical-induced disease (CID) relations.

Authors

  • Yifan Peng
    Department of Population Health Sciences, Weill Cornell Medicine, New York, USA.
  • Chih-Hsuan Wei
    National Center for Biotechnology Information, Bethesda, MD 20894 USA.
  • Zhiyong Lu
    National Center for Biotechnology Information, Bethesda, MD 20894 USA.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals