AuDis: an automatic CRF-enhanced disease normalization in biomedical text

@inproceedings{Lee2016AuDisAA,
  title={AuDis: an automatic CRF-enhanced disease normalization in biomedical text},
  author={Hsin-Chun Lee and Yi-Yu Hsu and Hung-Yu Kao},
  booktitle={Database},
  year={2016}
}
Diseases play central roles in many areas of biomedical research and healthcare. Consequently, aggregating the disease knowledge and treatment research reports becomes an extremely critical issue, especially in rapid-growth knowledge bases (e.g. PubMed). We therefore developed a system, AuDis, for disease mention recognition and normalization in biomedical texts. Our system utilizes an order two conditional random fields model. To optimize the results, we customize several post-processing steps… CONTINUE READING
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