Work

Determining the syntactic structure of medical terms in clinical notes

Year: 2007

Type: conference-paper

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.

DOI: 10.3115/1572392.1572395

Authors: Bridget T. McInnes, Ted Pedersen, Serguei V. Pakhomov

Institutions: University of Minnesota, University of Minnesota, Duluth

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Funder: National Science Foundation

Award: Automatic Resolution of Semantic Ambiguity in Natural Language

OpenAlex ID: W1965745145

FWCI: 2.908

Cites: 24

Cited by: 7

Related to: 10