Fleur Mougin1, Natalia Grabar2. 1. ISPED, Université de Bordeaux 2, Bordeaux, France ERIAS, INSERM, Centre INSERM U897, Bordeaux, France. 2. CNRS UMR 8163 STL, Université Lille 1 and 3, Villeneuve d'Ascq, France.
Abstract
OBJECTIVE: This work focuses on multiply-related Unified Medical Language System (UMLS) concepts, that is, concepts associated through multiple relations. The relations involved in such situations are audited to determine whether they are provided by source vocabularies or result from the integration of these vocabularies within the UMLS. METHODS: We study the compatibility of the multiple relations which associate the concepts under investigation and try to explain the reason why they co-occur. Towards this end, we analyze the relations both at the concept and term levels. In addition, we randomly select 288 concepts associated through contradictory relations and manually analyze them. RESULTS: At the UMLS scale, only 0.7% of combinations of relations are contradictory, while homogeneous combinations are observed in one-third of situations. At the scale of source vocabularies, one-third do not contain more than one relation between the concepts under investigation. Among the remaining source vocabularies, seven of them mainly present multiple non-homogeneous relations between terms. Analysis at the term level also shows that only in a quarter of cases are the source vocabularies responsible for the presence of multiply-related concepts in the UMLS. These results are available at: http://www.isped.u-bordeaux2.fr/ArticleJAMIA/results_multiply_related_concepts.aspx. DISCUSSION: Manual analysis was useful to explain the conceptualization difference in relations between terms across source vocabularies. The exploitation of source relations was helpful for understanding why some source vocabularies describe multiple relations between a given pair of terms. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
OBJECTIVE: This work focuses on multiply-related Unified Medical Language System (UMLS) concepts, that is, concepts associated through multiple relations. The relations involved in such situations are audited to determine whether they are provided by source vocabularies or result from the integration of these vocabularies within the UMLS. METHODS: We study the compatibility of the multiple relations which associate the concepts under investigation and try to explain the reason why they co-occur. Towards this end, we analyze the relations both at the concept and term levels. In addition, we randomly select 288 concepts associated through contradictory relations and manually analyze them. RESULTS: At the UMLS scale, only 0.7% of combinations of relations are contradictory, while homogeneous combinations are observed in one-third of situations. At the scale of source vocabularies, one-third do not contain more than one relation between the concepts under investigation. Among the remaining source vocabularies, seven of them mainly present multiple non-homogeneous relations between terms. Analysis at the term level also shows that only in a quarter of cases are the source vocabularies responsible for the presence of multiply-related concepts in the UMLS. These results are available at: http://www.isped.u-bordeaux2.fr/ArticleJAMIA/results_multiply_related_concepts.aspx. DISCUSSION: Manual analysis was useful to explain the conceptualization difference in relations between terms across source vocabularies. The exploitation of source relations was helpful for understanding why some source vocabularies describe multiple relations between a given pair of terms. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Keywords:
Artificial Intelligence; Systems Integration; Terminology; Terminology auditing; Unified Medical Language System
Authors: Huanying Helen Gu; George Hripcsak; Yan Chen; C Paul Morrey; Gai Elhanan; James Cimino; James Geller; Yehoshua Perl Journal: AMIA Annu Symp Proc Date: 2007-10-11