Using lexical, terminological and ontological resources for entity recognition tasks in the medical domain

Authors:
Maria Taboada;Maria Meizoso;Diego Martínez;José J. Des
Affiliations:
Dpto. de Electrónica e Computación, Universidad de Santiago de Compostela, Santiago de Compostela, Spain;Dpto. de Electrónica e Computación, Universidad de Santiago de Compostela, Santiago de Compostela, Spain and Dpto. de Computación, Universidad de A Coruña, A Coruña, Spain;Dpto. de Física Aplicada, Universidad de Santiago de Compostela, Lugo, Spain;Servicio de Oftalmología, Hospital Comarcal de Monforte, Spain
Venue:
AIME'07 Proceedings of the 2007 conference on Knowledge management for health care procedures
Year:
2007

Citing 3
Cited 0

Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method

Computers and Biomedical Research
BioRAT: extracting biological information from full-length papers

Bioinformatics
METHODOLOGICAL REVIEW: Approaches for creating computer-interpretable guidelines that facilitate decision support

Artificial Intelligence in Medicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reports on a case-study of applying various publicly available resources (lexical, terminological and ontological) for medical recognition tasks, that is, for identifying medical entities in the analysis of clinical practice guideline texts. The paper provides a methodological support that systematises the entity recognition task in the medical domain. Preliminary analysis shows that many of the medical linguistic expressions describing goals and intentions in natural language are included in the current terminological resources. So, these resources can be used as a means of disambiguating and structuring this type of expressions, with the final aim of indexing guideline repositories for efficient searching.