AI as a resource for the clarification of medical terminology
Abstract Medical terminology is perceived as an obstacle for patients and family members to understand the medical message. In this context, plain language advocates for making specialised knowledge accessible to citizens. This article puts the synergy between medical terminology, plain language, and computational linguistics (a branch of Artificial Intelligence) on the table. Our purpose is to determine if Generative AI applications, like ChatGPT, can assist in creating glossaries of terms with their corresponding simple variants. For this, a relevant sub-field of medicine, cardiology, was taken as a case study, even though it could be extrapolated to other sub-fields. Next, a glossary of key cardiology terms was created following a classic methodological approach. Then, the most relevant phases of the process (terminology extraction, search for synonyms, and selection of the clearest synonym) were reproduced using ChatGPT. The results of the comparative study between both approaches give a glimpse of the extent to which this technology can be a useful resource for creating glossaries that can be employed for writing using plain language.
Authors
- Laia Vidal Sabanés
- Iria da Cunha (ORCID: https://orcid.org/0000-0002-7707-1574)
Institutions
- Universitat Pompeu Fabra (ES)
- Distance State University (CR)
- Centre Universitaire de Mila (DZ)
- Université de Montréal (CA)
Publication Details
- Journal
- Terminology International Journal of Theoretical and Applied Issues in Specialized Communication
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1075/term.00083.vid
- Citations
- 1
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.81