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Text normalization in clinical natural language processing includes the task to identify acronyms to obtain their appropriate expanded form. This paper contributes to acronym resolution in Spanish through the creation of a data resource that facilitates acronym resolution. It is based on a set of acronym dictionaries classified by clinical speci…

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Leveraging pubmed to create a specialty-based sense inventory for spanish acronym resolution

Acronyms frequently occur in clinical text, which makes their identification, disambiguation and resolution an important task in clinical natural language processing. This paper contributes to acronym resolution in Spanish through the creation of a set of sense inventories organized by clinical specialty containing acronyms, their expansions, and corpus-driven features. The new acronym resource is composed of 51 clinical specialties with 3,603 acronyms in total, from which we identified 228 language independent acronyms and 391 language dependent expansions. We further analyzed the sense inventory across specialties and present novel insights of acronym usage in biomedical Spanish texts.

Authors

  • Alexandra Pomares-Quimbaya
  • Pilar López-Úbeda
  • Michel Oleynik
  • Stefan Schulz

Citing

If you use the lexicon in your research, please cite: Leveraging PubMed to Create a Specialty-Based Sense Inventory for Spanish Acronym Resolution.

@incollection{pomares2020leveraging,
  title={Leveraging pubmed to create a specialty-based sense inventory for spanish acronym resolution},
  author={Pomares-Quimbaya, Alexandra and L{\'o}pez-{\'U}beda, Pilar and Oleynik, Michel and Schulz, Stefan},
  booktitle={Digital Personalized Health and Medicine},
  pages={292--296},
  year={2020},
  publisher={IOS Press}
}

About

Text normalization in clinical natural language processing includes the task to identify acronyms to obtain their appropriate expanded form. This paper contributes to acronym resolution in Spanish through the creation of a data resource that facilitates acronym resolution. It is based on a set of acronym dictionaries classified by clinical speci…

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