Document Detail


Associating Clinical Archetypes Through UMLS Metathesaurus Term Clusters.
MedLine Citation:
PMID:  20827566     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
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.
Authors:
Leonardo Lezcano; Salvador Sánchez-Alonso; Miguel-Angel Sicilia
Related Documents :
8759466 - Towards a texture naming system: identifying relevant dimensions of texture.
12059666 - Beyond blobs in percolation cluster structure: the distribution of 3-blocks at the perc...
16127096 - Individual fecundity and senescence in drosophila and medfly.
9419316 - Globular clusters, hipparcos, and the age of the galaxy.
23800216 - Where do features come from?
19905256 - Lattice boltzmann model for axisymmetric thermal flows.
Publication Detail:
Type:  Journal Article     Date:  2010-09-09
Journal Detail:
Title:  Journal of medical systems     Volume:  36     ISSN:  0148-5598     ISO Abbreviation:  J Med Syst     Publication Date:  2012 Jun 
Date Detail:
Created Date:  2012-05-07     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7806056     Medline TA:  J Med Syst     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1249-58     Citation Subset:  IM    
Affiliation:
Information Engineering Research Unit, Computer Science Department, University of Alcalá, Alcalá, Spain, leonardo.lezcano@uah.es.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Automatic Detection of the Existence of Subarachnoid Hemorrhage from Clinical CT Images.
Next Document:  3D Matrix Pattern Based Support Vector Machines for Identifying Pulmonary Cancer in CT Scanned Image...