Extraction of disease-treatment semantic relations from biomedical sentences

Authors:
Oana Frunza;Diana Inkpen
Affiliations:
University of Ottawa Ottawa, ON, Canada;University of Ottawa Ottawa, ON, Canada
Venue:
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Year:
2010

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Abstract

This paper describes our study on identifying semantic relations that exist between diseases and treatments in biomedical sentences. We focus on three semantic relations: Cure, Prevent, and Side Effect. The contributions of this paper consists in the fact that better results are obtained compared to previous studies and the fact that our research settings allow the integration of biomedical and medical knowledge. We obtain 98.55% F-measure for the Cure relation, 100% F-measure for the Prevent relation, and 88.89% F-measure for the Side Effect relation.