IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v13y2023i1p21582440221148454.html
   My bibliography  Save this article

Analysis of Context-Dependent Errors in the Medical Domain in Spanish: A Corpus-Based Study

Author

Listed:
  • Jésica López Hernández
  • Fernando Molina Molina
  • Ã ngela Almela

Abstract

This corpus-based study aimed to investigate the presence of context-dependent linguistic errors in a corpus of clinical reports. The data were taken from a corpus comprising more than 2 million words and made up of clinical reports from emergency medicine, intensive care unit, general surgery, and psychiatry. Quantitative and qualitative analyses were carried out. A language model based on n-grams was developed for the detection of errors, parameters for the selection of cases were defined, and a classification tool was implemented. The findings indicated that emergency medicine was the medical specialty with the highest number of context-dependent errors and that the most frequent type of error was omission of written accent. Furthermore, the analysis revealed the presence of errors of competence due to the incorrect application of the linguistic norm of Spanish, phenomena of phonetic similarity, and composition of words; it is also worth noting that performance errors occurred due to rapid typing on the keyboard. This study constituted the first analysis and creation of a typology of context-dependent errors for the medical domain in Spanish. It contributed to the design of a module based on linguistic knowledge that can be used for the development and improvement of automatic correction systems that, in turn, are used for data processing in medicine.

Suggested Citation

  • Jésica López Hernández & Fernando Molina Molina & à ngela Almela, 2023. "Analysis of Context-Dependent Errors in the Medical Domain in Spanish: A Corpus-Based Study," SAGE Open, , vol. 13(1), pages 21582440221, January.
    • Handle: RePEc:sae:sagope:v:13:y:2023:i:1:p:21582440221148454
    DOI: 10.1177/21582440221148454
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440221148454
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440221148454?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:13:y:2023:i:1:p:21582440221148454. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.