Chemical-induced disease extraction via convolutional neural networks with attention

@article{Li2017ChemicalinducedDE,
  title={Chemical-induced disease extraction via convolutional neural networks with attention},
  author={Haodi Li and Qingcai Chen and Buzhou Tang and Xiaolong Wang},
  journal={2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
  year={2017},
  pages={1276-1279}
}
Extracting relationships between chemicals and diseases from unstructured literature is very important for many biomedical applications such as pharmacovigilance and drug repositioning. Automatic chemical-induced disease extraction is usually recognized as a classification task, and several systems have been proposed for this task recently due to some annotated corpora publicly available. Most of the systems are based on machine learning methods with many manually-crafted features. In recent… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-2 of 2 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 13 references

Biomedical Relation Extraction: From Binary to Complex

Comp. Math. Methods in Medicine • 2014
View 1 Excerpt

Similar Papers

Loading similar papers…