ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2015
NEO: Systematic Non-Lattice Embedding of Ontologies for Comparing the Subsumption Relationship in SNOMED CT and in FMA Using MapReduce.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Extending import detection algorithms for concept import from two to three biomedical terminologies.BMC medical informatics and decision making · 2020Article
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Mining Relation Reversals in the Evolution of SNOMED CT Using MapReduce.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.AMIA ... Annual Symposium proceedings. AMIA SymposiumArticle
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Authors and funding
5 authors.
Funding
Abstract
A structural disparity of the subsumption relationship between FMA and SNOMED CT's Body Structure sub-hierarchy is that while the is-a relation in FMA has a tree structure, the corresponding relation in Body Structure is not even a lattice. This paper introduces a method called NEO, for non-lattice embedding of FMA fragments into the Body Structure sub-hierarchy to understand (1) this structural disparity, and (2) its potential utility in analyzing non-lattice fragments in SNOMED CT. NEO consists of four steps. First, transitive, upper- and down-closures are computed for FMA and SNOMED CT using MapReduce, a modern scalable distributed computing technique. Secondly, UMLS mappings between FMA and SNOMED CT concepts are used to identify equivalent concepts in non-lattice fragments from Body Structure. Then, non-lattice fragments in the Body Structure sub-hierarchy are extracted, and FMA concepts matching those in the non-lattice fragments are used as the seeds to generate the corresponding FMA fragments. Lastly, the corresponding FMA fragments are embedded to the non-lattice fragments for comparative visualization and analysis. After identifying 8,428 equivalent concepts between the collection of over 30,000 concepts in Body Structure and the collection of over 83,000 concepts in FMA using UMLS equivalent concept mappings, 2,117 shared is-a relations and 5,715 mismatched relations were found. Among Body Structure's 90,465 non-lattice fragments, 65,968 (73%) contained one or more is-a relations that are in SNOMED CT but not in FMA, even though they have equivalent source and target concepts. This shows that SNOMED CT may be more liberal in classifying a relation as is-a, a potential explanation for the fragments not conforming to the lattice property.
Identifiers
26306275PMC4525277What OpenQuestion holds
Registered trials
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