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.
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CITATION STYLE
Grön, L., Bertels, A., & Heylen, K. (2019). Leveraging sublanguage features for the semantic categorization of clinical terms. In BioNLP 2019 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 18th BioNLP Workshop and Shared Task (pp. 211–216). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-5022
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