Facilitating SNOMED-CT Template Creation by Targeting Stopwords

Rashmi Burse, Michela Bertolotto, Gavin McArdle

2023

Abstract

Quality Assurance (QA) of biomedical ontologies is a major challenge in the health-informatics domain. One of the preliminary ways in which we can maintain the quality of a biomedical ontology is by ensuring consistency in the modelling styles of biomedical concepts. Maintaining consistency in the lexical, structural and ontological modelling of biomedical concepts reduces a concept’s susceptibility to errors. SNOMED-CT, which is one of the most widely adopted biomedical ontologies, strives to achieve this consistency by creating templates for logical definitions based on the description of biomedical concept names. The work presented here in based on the observation that the majority of the SNOMED-CT templates contain stopwords (non-medical terms) in their description that indicate a relationship between two medical concepts. We hypothesize that the process of creating SNOMED-CT templates can be automated to a large extent by targeting stopwords. In this work, we present a method that exploits stopwords in concept names to create templates for the structural and logical modelling of lexically and semantically similar biomedical concepts. The results have shown promising potential by extracting a multitude of SNOMED-CT templates, exhibiting more than 200 templates for the stopword of. Given the high demand for QA of biomedical ontologies, these results are highly beneficial in automating the existing mechanisms employed in maintaining consistency in the modeling of SNOMED-CT concepts. The presented method can be used as a complementary process to mitigate the manual efforts of SNOMED-CT curators. Furthermore, auditing potentially incomplete definitions of SNOMED-CT concepts using the extracted templates has identified 49-87% inconsistent concepts for the stopwords of and in in the biomedical ontology.

Paper Citation

in Harvard Style

Burse R., Bertolotto M. and McArdle G. (2023). Facilitating SNOMED-CT Template Creation by Targeting Stopwords. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF; ISBN 978-989-758-631-6, SciTePress, pages 279-286. DOI: 10.5220/0011660500003414

in Bibtex Style

@conference{healthinf23,
author={Rashmi Burse and Michela Bertolotto and Gavin McArdle},
title={Facilitating SNOMED-CT Template Creation by Targeting Stopwords},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF},
year={2023},
pages={279-286},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011660500003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF
TI - Facilitating SNOMED-CT Template Creation by Targeting Stopwords
SN - 978-989-758-631-6
AU - Burse R.
AU - Bertolotto M.
AU - McArdle G.
PY - 2023
SP - 279
EP - 286
DO - 10.5220/0011660500003414
PB - SciTePress