A sequence labeling approach to link medications and their attributes in clinical notes and clinical trial announcements for information extraction.

CONCLUSIONS: We compared the novel MLSL method with a binary classification and a rule-based method. The MLSL method performed statistically significantly better than the rule-based method. However, the SVM-based binary classification method was statistically significantly better than the MLSL method for both the CTA and CN corpora. Using parsimonious feature sets both the SVM-based binary classification and CRF-based MLSL methods achieved high performance in detecting medication name and attribute linkages in CTA and CN.
PMID: 23268488 [PubMed - as supplied by publisher]

Source: Journal of the American Medical Informatics Association - December 25, 2012 Category: Information Technology Authors: Li Q, Zhai H, Deleger L, Lingren T, Kaiser M, Stoutenborough L, Solti I Tags: J Am Med Inform Assoc Source Type: research