ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2022
A substring replacement approach for identifying missing IS-A relations in SNOMED CT.
Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Quantitatively assessing the impact of the quality of SNOMED CT subtype hierarchy on cohort queries.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.Journal of biomedical semantics · 2024Article
- An Automated Approach for Identifying Erroneous IS-A Relations in SNOMED CT.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Identifying Missing IS-A Relations in SNOMED CT with Fine-Tuned Pre-trained Language Models and Non-lattice Subgraphs.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
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4 authors.
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Abstract
Biomedical ontologies provide formalized information and knowledge in the biomedical domain. Over the years, biomedical ontologies have played an important role in facilitating biomedical research and applications. Common quality issues of biomedical ontologies include inconsistent naming of concepts, redundant concepts, redundant relations, incomplete/incorrect concept definitions, and incomplete/incorrect class hierarchies. In this work, we focus on addressing the incompleteness of the class hierarchy in SNOMED CT. We develop a substring replacement approach, leveraging concepts' lexical features and existing IS-A relations to identify potential missing IS-A relations in SNOMED CT. To evaluate the effectiveness of our approach, we performed both automated and manual validation. For the automated evaluation, we leverage relations from external terminologies in the Unified Medical Language System (UMLS) to validate the identified missing IS-A relations. For the manual validation, a randomly selected 100 samples from the results are reviewed by a domain expert. Applying our approach to the March 2022 release of SNOMED CT US Edition, we identified 3,228 potential missing IS-A relations, among which 63 were validated through the UMLS. The evaluation by the domain expert revealed that 89 out of 100 (a precision of 89%) missing IS-A relations are valid cases, showing the effectiveness of this substring replacement approach to facilitate the quality assurance of IS-A relations in SNOMED CT.
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