Associating clinical archetypes through UMLS Metathesaurus term clusters.
Clinical archetypes are modular definitions of clinical data, expressed using standard or open constraint-based data models as the CEN EN13606 and openEHR. There is an increasing archetype specification activity that raises the need for techniques to associate archetypes to support better management and user navigation in archetype repositories. This paper reports on a computational technique to generate tentative archetype associations by mapping them through term clusters obtained from the UMLS Metathesaurus. The terms are used to build a bipartite graph model and graph connectivity measures can be used for deriving associations.
Lezcano
Leonardo
L
Computer Science Department, University of Alcalá, Alcalá, Spain. leonardo.lezcano@uah.es
Sánchez-Alonso
Salvador
S
Sicilia
Miguel-Angel
MA
D057286:Electronic Health Records; D016347:Medical Records Systems, Computerized; D012660:Semantics; D017432:Unified Medical Language System
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