Paper: Medical Entity Recognition: A Comparaison of Semantic and Statistical Methods

ACL ID W11-0207
Title Medical Entity Recognition: A Comparaison of Semantic and Statistical Methods
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2011
Authors

Medical Entity Recognition is a crucial step towards efficient medical texts analysis. In this paper we present and compare three methods based on domain-knowledge and machine-learning techniques. We study two research directions through these approaches: (i) a first direction where noun phrases are extracted in a first step with a chunker be- fore the final classification step and (ii) a sec- ond direction where machine learning tech- niques are used to identify simultaneously en- tities boundaries and categories. Each of the presented approaches is tested on a standard corpus of clinical texts. The obtained results show that the hybrid approach based on both machine learning and domain knowledge ob- tains the best performance.