This paper demonstrates a method for determining the syntactic structure of medical terms. We use a model-fitting method based on the Log Likelihood Ratio to classify three-word medical terms as right or left-branching. We validate this method by computing the agreement between the classification produced by the method and manually annotated classifications. The results show an agreement of 75% - 83%. This method may be used effectively to enable a wide range of applications that depend on the semantic interpretation of medical terms including automatic mapping of terms to standardized vocabularies and induction of terminologies from unstructured medical text.
|Original language||English (US)|
|Number of pages||8|
|State||Published - 2007|
|Event||ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 - Prague, Czech Republic|
Duration: Jun 29 2007 → …
|Other||ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007|
|Period||6/29/07 → …|
Bibliographical noteFunding Information:
This research was supported in part by the NLM Training Grant in Medical Informatics (T15 LM07041-19). Ted Pedersen’s participation in this project was supported by the NSF Faculty Early Career Development Award (#0092784).