Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms
Ver/ Abrir
Impacto
Scholar |
Otros documentos de la autoría: Quesada-Martínez, Manuel; Marcos, Mar; Abad-Navarro, Francisco; Martínez-Salvador, Begoña; Fernández Breis, Jesualdo Tomás
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/146069
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological termsAutoría
Fecha de publicación
2018-12-05Editor
American Medical Informatics AssociationISSN
1942-597XCita bibliográfica
QUESADA-MARTÍNEZ, Manuel, et al. Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms. In: AMIA Annual Symposium Proceedings. American Medical Informatics Association, 2018. p. 922Tipo de documento
info:eu-repo/semantics/conferenceObjectVersión de la editorial
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371308/Versión
info:eu-repo/semantics/publishedVersionResumen
Clinical Practice Guidelines (CPGs) contain recommendations intended to optimize patient care, produced based on a systematic review of evidence. In turn, Computer-Interpretable Guidelines (CIGs) are formalized versions ... [+]
Clinical Practice Guidelines (CPGs) contain recommendations intended to optimize patient care, produced based on a systematic review of evidence. In turn, Computer-Interpretable Guidelines (CIGs) are formalized versions of CPGs for use as decision-support systems. We consider the enrichment of the CIG by means of an OWL ontology that describes the clinical domain of the CIG, which could be exploited e.g. for the interoperability with the Electronic Health Record (EHR). As a first step, in this paper we describe a method to support the development of such an ontology starting from a CIG. The method uses an alignment algorithm for the automated identification of ontological terms relevant to the
clinical domain of the CIG, as well as a web platform to manually review the alignments and select the appropriate ones. Finally, we present the results of the application of the method to a small corpus of CIGs. [-]
Descripción
Ponència presentada a 2018 The American Medical Informatics Association Annual Symposium (AMIA 2018) celebrat a San Francisco, Estats Units de l'Amèrica del Nord, el 3 de novembre de 2018
Derechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess