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Coping with the Variability of Medical Terms (2004)
BibTeX
@MISC{(eds04copingwith,
author = {M. Fieschi Et Al. (eds and Robert H Baud and Patrick Ruch and Arnaud Gaudinat and Paul Fabry and Christian Lovis and Antoine Geissbuhler and Robert H Baud},
title = {Coping with the Variability of Medical Terms},
year = {2004}
}
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Abstract
Objectives: To cope with medical terms, which present a high variability of expression through a single natural language, in the sense that any term may be reformulated in hundred of different ways. Methods: A typology of term variants is presented as a systematic approach in order to favour the implementation of an exhaustive solution. Then, an algorithm able to handle all variants is designed. Results: Using MetaMap, single terms are analyzed with a success rate varying between 68 and 88 %; the algorithm presented in this paper improves this situation. Conclusions: This experience shows that a semantic driven method, based on a thesaurus, provides a satisfactory solution to the problem of variability of a single term. The presented typology is representative of most variants in a language. Keywords: Natural language processing, text retrieval, knowledge representation.
Keyphrases
medical term single term different way success rate exhaustive solution natural language processing term variant satisfactory solution systematic approach high variability text retrieval presented typology knowledge representation semantic driven method single natural language using metamap
