Abstract
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) |
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| Pages | 9-16 |
| Number of pages | 8 |
| DOIs | |
| State | Published - 2007 |
| Event | ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 - Prague, Czech Republic Duration: Jun 29 2007 → … |
Other
| Other | ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 |
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| Country/Territory | Czech Republic |
| City | Prague |
| Period | 6/29/07 → … |
Bibliographical note
Funding 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).
Publisher Copyright:
© 2007 Association for Computational Linguistics.