ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2009
Detecting Underspecification in SNOMED CT concept definitions through natural language processing.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- Article
- Identifying Missing Hierarchical Relations in SNOMED CT from Logical Definitions Based on the Lexical Features of Concept Names.CEUR workshop proceedings · 2016Article
- Article
- Auditing complex concepts of SNOMED using a refined hierarchical abstraction network.Journal of biomedical informatics · 2012Review
- Dissimilarities in the Logical Modeling of Apparently Similar Concepts in SNOMED CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quality assurance and audit issues play a major role in maintening large biomedical terminology, such as SNOMED CT. Several automatized techniques have been proposed to facilitate the identification of weak spots and suggest adequate improvements.In this study, we address a well-known issue within SNOMED CT: Albeit the wording of many free-text concept descriptions suggests a connection to other concepts, they are often not referred to in the logical concept definition.To detect such inconsistencies, we use a semantic indexing approach which maps free text onto a sequence of semantic identifiers. Applied to SNOMED CT concepts without attributes, our technique spots refinable concepts and suggests appropriate attributes, i.e., connections to other concepts. Based on a manual analysis of random samples, we estimate that approximately 18,000 refinable concepts can be found.
Indexed as
Identifiers
20351905PMC2815431What OpenQuestion holds
Registered trials
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