Improving textual medication extraction using combined conditional random fields and rule-based systems

@article{Tikk2010ImprovingTM,
  title={Improving textual medication extraction using combined conditional random fields and rule-based systems},
  author={Domonkos Tikk and Ill{\'e}s Solt},
  journal={Journal of the American Medical Informatics Association : JAMIA},
  year={2010},
  volume={17 5},
  pages={540-4}
}
OBJECTIVE In the i2b2 Medication Extraction Challenge, medication names together with details of their administration were to be extracted from medical discharge summaries. DESIGN The task of the challenge was decomposed into three pipelined components: named entity identification, context-aware filtering and relation extraction. For named entity identification, first a rule-based (RB) method that was used in our overall fifth place-ranked solution at the challenge was investigated. Second, a… CONTINUE READING
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Proceedingsof the 19th Conference on Uncertainty in Artificial Intelligence; 7e10 August 2003

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  • Acapulco, Mexico; San Francisco: Morgan Kaufmann…
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