Issues in mapping LOINC laboratory tests to SNOMED CT.
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Comprehensive clinical terminologies such as SNOMED CT tend to overlap with specialized terminologies such as LOINC (e.g., for the domain of laboratory procedures). Terminological systems such as the UMLS are often used to bridge between terminologies. However, the integration of LOINC in the UMLS and with other terminologies remains suboptimal. We mapped concepts for laboratory tests from LOINC to pre-coordinated SNOMED CT concepts, based on shared relations to other concepts. As LOINC is finer-grained than SNOMED CT, several LOINC codes tend to map to the same SNOMED CT concept. However, a large proportion of LOINC codes could not be mapped to SNOMED CT through this approach, because of underspecified definitions in SNOMED CT and a lack of fine-grained, pre-coordinated concepts in SNOMED CT. (+info)
Comparison of ontology-based semantic-similarity measures.
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Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. Such a comparison can offer insight on the validity of different approaches. We compared 3 approaches to semantic similarity-metrics (which rely on expert opinion, ontologies only, and information content) with 4 metrics applied to SNOMED-CT. We found that there was poor agreement among those metrics based on information content with the ontology only metric. The metric based only on the ontology structure correlated most with expert opinion. Our results suggest that metrics based on the ontology only may be preferable to information-content-based metrics, and point to the need for more research on validating the different approaches. (+info)
Forty years of SNOMED: a literature review.
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