ArticleJournal of biomedical semantics2014
A framework for assessing the consistency of drug classes across sources.
Article in Journal of biomedical semantics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Problems associated with the ATC system of drug classification.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Alignment of vaccine codes using an ontology of vaccine descriptions.Journal of biomedical semantics · 2022Article
- Evaluating the performance of drug-repurposing technologies.Drug discovery today · 2022Review
- A 2018 workshop: vaccine and drug ontology studies (VDOS 2018).BMC bioinformatics · 2019Article
- Rebuilding the Standing Prescription Renewal Orders.Applied clinical informatics · 2019Article
- Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT.Studies in health technology and informatics · 2017Article
- Leveraging MEDLINE indexing for pharmacovigilance - Inherent limitations and mitigation strategies.Journal of biomedical informatics · 2015Article
- A 2013 workshop: vaccine and drug ontology studies (VDOS 2013).Journal of biomedical semantics · 2014Article
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2 authors.
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Abstract
backgroundThe objective of this study is to develop a framework for assessing the consistency of drug classes across sources, such as MeSH and ATC. Our framework integrates and contrasts lexical and instance-based ontology alignment techniques. Moreover, we propose metrics for assessing not only equivalence relations, but also inclusion relations among drug classes.
resultsWe identified 226 equivalence relations between MeSH and ATC classes through the lexical alignment, and 223 through the instance-based alignment, with limited overlap between the two (36). We also identified 6,257 inclusion relations. Discrepancies between lexical and instance-based alignments are illustrated and discussed.
conclusionsOur work is the first attempt to align drug classes with sophisticated instance-based techniques, while also distinguishing between equivalence and inclusion relations. Additionally, it is the first application of aligning drug classes in ATC and MeSH. By providing a detailed account of similarities and differences between drug classes across sources, our framework has the prospect of effectively supporting the creation of a mapping of drug classes between ATC and MeSH by domain experts.
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