Abstract
The automatic processing of clinical documents, such as Electronic Health Records (EHRs), could benefit substantially from the enrichment of medical terminologies with terms encountered in clinical practice. To integrate such terms into existing knowledge sources, they must be linked to corresponding concepts. We present a method for the semantic categorization of clinical terms based on their surface form. We find that features based on sublanguage properties can provide valuable cues for the classification of term variants.- Anthology ID:
- W19-5022
- Volume:
- Proceedings of the 18th BioNLP Workshop and Shared Task
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii
- Venue:
- BioNLP
- SIG:
- SIGBIOMED
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 211–216
- Language:
- URL:
- https://aclanthology.org/W19-5022
- DOI:
- 10.18653/v1/W19-5022
- Cite (ACL):
- Leonie Grön, Ann Bertels, and Kris Heylen. 2019. Leveraging Sublanguage Features for the Semantic Categorization of Clinical Terms. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 211–216, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Leveraging Sublanguage Features for the Semantic Categorization of Clinical Terms (Grön et al., BioNLP 2019)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/W19-5022.pdf