Paper: Exploring Surface-Level Heuristics for Negation and Speculation Discovery in Clinical Texts

ACL ID W10-1910
Title Exploring Surface-Level Heuristics for Negation and Speculation Discovery in Clinical Texts
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2010
Authors

We investigate the automatic identification of negated and speculative statements in biomedical texts, focusing on the clinical domain. Our goal is to evaluate the perfor- mance of simple, Regex-based algorithms that have the advantage of low compu- tational 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 re- sults (evaluated on the BioScope corpus). Current and future work focuses on a boot- strapping algorithm for the discovery of new rules from unannotated clinical texts. 1 Motivation Finding negated and speculative (hedging) state- ments is an important subtask for biomedical In- formation Extraction (...