Determining the syntactic structure of medical terms in clinical notes

Bridget T. McInnes, Ted Pedersen, Serguei V Pakhomov

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

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 languageEnglish (US)
Pages9-16
Number of pages8
DOIs
StatePublished - 2007
EventACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007 - Prague, Czech Republic
Duration: Jun 29 2007 → …

Other

OtherACL 2007 Workshop on Biological, Translational, and Clinical Language Processing, BioNLP 2007
CountryCzech Republic
CityPrague
Period6/29/07 → …

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).

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