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Pac Symp Biocomput. 2002:350-61.

Filling preposition-based templates to capture information from medical abstracts.

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  • 1Department of Management Information Systems, University of Arizona, 1030 E. Helen St, Tucson, AZ 85721, USA.

Abstract

Due to the recent explosion of information in the biomedical field, it is hard for a single researcher to review the complex network involving genes, proteins, and interactions. We are currently building GeneScene, a toolkit that will assist researchers in reviewing existing literature, and report on the first phase in our development effort: extracting the relevant information from medical abstracts. We are developing a medical parser that extracts information, fills basic prepositional-based templates, and combines the templates to capture the underlying sentence logic. We tested our parser on 50 unseen abstracts and found that it extracted 246 templates with a precision of 70%. In comparison with many other techniques, more information was extracted without sacrificing precision. Future improvement in precision will be achieved by correcting three categories of errors.

PMID:
11928489
[PubMed - indexed for MEDLINE]
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