Limits...
NEO: Systematic Non-Lattice Embedding of Ontologies for Comparing the Subsumption Relationship in SNOMED CT and in FMA Using MapReduce.

Zhu W, Zhang GQ, Tao S, Sun M, Cui L - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of EECS, Case Western Reserve University, Cleveland, OH Division of Medical Informatics, Case Western Reserve University, Cleveland, OH.

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.

No MeSH data available.


10 frequently mismatched relations in FMA occurring in non-lattice fragments in SNOMED CT as is-a relation.
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f5-2092163: 10 frequently mismatched relations in FMA occurring in non-lattice fragments in SNOMED CT as is-a relation.

Mentions: Among 90,465 non-lattice fragments in SNOMD CT’s Body Structure [11], 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 subsumption, which may cause the fragments not conforming the lattice property. Fig. 5 shows 10 frequently mismatched relations in SNOMED CT (is-a) and FMA (not is-a). For example, the relationship of Structure of pelvic viscus and Structure of abdominal viscus has a is-a relation in SNOMED CT, but “member of” relation in FMA.


NEO: Systematic Non-Lattice Embedding of Ontologies for Comparing the Subsumption Relationship in SNOMED CT and in FMA Using MapReduce.

Zhu W, Zhang GQ, Tao S, Sun M, Cui L - AMIA Jt Summits Transl Sci Proc (2015)

10 frequently mismatched relations in FMA occurring in non-lattice fragments in SNOMED CT as is-a relation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525277&req=5

f5-2092163: 10 frequently mismatched relations in FMA occurring in non-lattice fragments in SNOMED CT as is-a relation.
Mentions: Among 90,465 non-lattice fragments in SNOMD CT’s Body Structure [11], 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 subsumption, which may cause the fragments not conforming the lattice property. Fig. 5 shows 10 frequently mismatched relations in SNOMED CT (is-a) and FMA (not is-a). For example, the relationship of Structure of pelvic viscus and Structure of abdominal viscus has a is-a relation in SNOMED CT, but “member of” relation in FMA.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of EECS, Case Western Reserve University, Cleveland, OH Division of Medical Informatics, Case Western Reserve University, Cleveland, OH.

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.

No MeSH data available.