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Título:
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Improving the usability of HL7 information models by automatic filtering
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Autor/a:
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Villegas Niño, Antonio; Olivé Ramon, Antoni; Vilalta, Josep
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació; Universitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació |
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Abstract:
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The amount of knowledge represented in theHealth Level 7 International (HL7) information models is very large. The sheer size of those models makes them very usefulfor the communities for which they are developed. However, the size of the models and their overall organization makes itdifficult to manually extract knowledge from them. We propose to extract that knowledge by using a novel filtering method that we have developed. Our method is based on the concept of class interest as a combination of class importance and class closeness. The application of our method automaticallyobtains a filtered information model of the whole HL7 models according to the user preferences. We show that the use of aprototype tool that implements that method and produces such filtered model improves the usability of the HL7 models due to its high precision and low computational time. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
-Health Level Seven International
-HL7
-Usabilitat
-ULM |
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Derechos:
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Tipo de documento:
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Artículo - Versión publicada
Objeto de conferencia |
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Editor:
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IEEE Computer Society Publications
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Compartir:
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