Exploring hedge identification in biomedical literature
Journal of Biomedical Informatics
The BioScope corpus: annotation for negation, uncertainty and their scope in biomedical texts
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Automatic extraction of lexico-syntactic patterns for detection of negation and speculation scopes
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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We investigate the automatic identification of negated and speculative statements in biomedical texts, focusing on the clinical domain. Our goal is to evaluate the performance of simple, Regex-based algorithms that have the advantage of low computational cost, simple implementation, and do not rely on the accurate computation of deep linguistic features of idiosyncratic clinical texts. The performance of the NegEx algorithm with an additional set of Regex-based rules reveals promising results (evaluated on the BioScope corpus). Current and future work focuses on a bootstrapping algorithm for the discovery of new rules from unannotated clinical texts.