Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Project deliverable . 2024
License: CC BY
Data sources: Datacite
ZENODO
Project deliverable . 2024
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Deliverable 3.4: Medical terminology

Authors: Costa, Rute; Vezzani, Federica; Di Nunzio, Giorgio Maria; Ramos, Margarida; Silva, Raquel; Carvalho, Sara; Canelas, Matilde; +3 Authors

Deliverable 3.4: Medical terminology

Abstract

This report outlines a methodology that addresses both conceptual and linguistic dimensions of terminology with the prime aim to enhance knowledge representation and promote informed communication within the medical domain, especially for the diseases under study in HEREDITARY. Foundational to this initiative is an approach that merges terminological theory with practical application. The theoretical underpinnings emphasize the dual nature of terminology: it operates both as a conceptual structure that reflects domain knowledge and a linguistic system of specialized terms. This conceptual-linguistic synergy ensures terminological accuracy, consistency, and clarity, ultimately improving the quality of healthcare information transfer. To demonstrate this dual-dimension approach we will go through an in-depth exploration of the gut-brain axis in existing biomedical terminological resources. The methods aim to illustrate how conceptual and linguistic structuring supports better domain understanding, corpus building, and expert engagement. Domain-corpus building and subsequent exploitation is a gateway to domain knowledge verbally expressed in texts written by experts. Hence, documenting the criteria, typologies, and metadata of gathered texts ensures a solid empirical foundation for terminology extraction. Various methods are presented for automatic and semi-automated term extraction. Tailored for the medical sector, these approaches address complexity and domain specificity, thus improving the precision and relevance of the extracted terms. Validating the terminology to ensure both linguistic accuracy and conceptual integrity is a core activity. By clarifying roles, processes, and the importance of citizen engagement, this validation step ensures that the resulting terminology is both authoritative and accessible to various user communities.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities