Annotating and Recognising Named Entities in Clinical Notes

@inproceedings{Wang2009AnnotatingAR,
  title={Annotating and Recognising Named Entities in Clinical Notes},
  author={Yefeng Wang},
  booktitle={ACL/IJCNLP},
  year={2009}
}
This paper presents ongoing research in clinical information extraction. This work introduces a new genre of text which are not well-written, noise prone, ungrammatical and with much cryptic content. A corpus of clinical progress notes drawn form an Intensive Care Service has been manually annotated with more than 15000 clinical named entities in 11 entity types. This paper reports on the challenges involved in creating the annotation schema, and recognising and annotating clinical named… CONTINUE READING
Highly Cited
This paper has 52 citations. REVIEW CITATIONS
36 Citations
25 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 36 extracted citations

52 Citations

051015'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 52 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 25 references

Snomed International

  • A. Côté, American Veterinary Medical Association, College of American Pathologists.
  • College of American Pathologists.
  • 2009

Integrated Annotation of Biomedical Text: Creating the PennBioIE corpus

  • M. Mandel
  • Text Mining Ontologies and Natural Language…
  • 2006
2 Excerpts

Similar Papers

Loading similar papers…