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Analyzing SNOMED CT's Historical Data: Pitfalls and Possibilities.
Ceusters, Werner; Bona, Jonathan P.
Afiliación
  • Ceusters W; Department of Biomedical Informatics, University at Buffalo, Buffalo, NY.
  • Bona JP; Department of Biomedical Informatics, University at Buffalo, Buffalo, NY.
AMIA Annu Symp Proc ; 2016: 361-370, 2016.
Article en En | MEDLINE | ID: mdl-28269831
ABSTRACT
SNOMED CT's Release Format 2 (RF2) has been announced as an improvement over its predecessor, for instance because of its more consistent and almost formal approach towards describing changes in components over different versions, as well as changes in the structure of SNOMED CT itself. We explore two sorts of changes that are only partially formalized in RF2 the relationships between associative relations and reasons for inactivations as expressed in Association Reference Sets and Attribute Value Reference Sets on the one hand, and the various patterns according to which semantic tags appearing in fully specified names change over subsequent versions with or without being related to inactivations. We propose a data conversion methodology that combines assertions about SNOMED CT components into history profiles and use elements of these profiles to build Formal Concept Analysis contexts to discover valid implications that can render implicit assumptions hidden in SNOMED CT's structure explicit.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Systematized Nomenclature of Medicine Idioma: En Revista: AMIA Annu Symp Proc Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Systematized Nomenclature of Medicine Idioma: En Revista: AMIA Annu Symp Proc Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article