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Ontological Representation of Laboratory Test Observables: Challenges and Perspectives in the SNOMED CT Observable Entity Model Adoption

Mary, Malissa (author)
BioMerieux, France; Univ Rouen, France
Soualmia, Lina F. (author)
Univ Rouen, France; LIMICS, France
Gansel, Xavier (author)
BioMerieux, France
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Darmoni, Stefan (author)
Univ Rouen, France; LIMICS, France
Karlsson, Daniel (author)
Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten
Schulz, Stefan (author)
Med Univ Graz, Austria
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 (creator_code:org_t)
2017-05-30
2017
English.
In: ARTIFICIAL INTELLIGENCE IN MEDICINE, AIME 2017. - Cham : SPRINGER INTERNATIONAL PUBLISHING AG. - 9783319597584 - 9783319597577 ; , s. 14-23
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • The emergence of electronic health records has highlighted the need for semantic standards for representation of observations in laboratory medicine. Two such standards are LOINC, with a focus on detailed encoding of lab tests, and SNOMED CT, which is more general, including the representation of qualitative and ordinal test results. In this paper we will discuss how lab observation entries can be represented using SNOMED CT. We use resources provided by the Regenstrief Institute and SNOMED International collaboration, which formalize LOINC terms as SNOMED CT post-coordinated expressions. We demonstrate the benefits brought by SNOMED CT to classify lab tests. We then propose a SNOMED CT based model for lab observation entries aligned with the BioTopLite2 (BTL2) upper level ontology. We provide examples showing how a model designed with no ontological foundation can produce misleading interpretations of inferred observation results. Our solution based on a BTL2 conformant formal interpretation of SNOMED CT concepts allows representing lab test without creating unintended models. We argue in favour of an ontologically explicit bridge between compositional clinical terminologies, in order to safely use their formal representations in intelligent systems.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Biomedical ontologies and terminologies; LOINC; SNOMED CT; BioTopLite2

Publication and Content Type

ref (subject category)
kon (subject category)

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