Paper Info
Title
A semi-automatic semantic method for mapping SNOMED CT concepts to VCM Icons.
Abstract
VCM (Visualization of Concept in Medicine) is an iconic language for representing key medical concepts by icons. However, the use of this language with reference terminologies, such as SNOMED CT, will require the mapping of its icons to the terms of these terminologies. Here, we present and evaluate a semi-automatic semantic method for the mapping of SNOMED CT concepts to VCM icons. Both SNOMED CT and VCM are compositional in nature; SNOMED CT is expressed in description logic and VCM semantics are formalized in an OWL ontology The proposed method involves the manual mapping of a limited number of underlying concepts from the VCM ontology, followed by automatic generation of the rest of the mapping. We applied this method to the clinical findings of the SNOMED CT CORE subset, and 100 randomly-selected mappings were evaluated by three experts. The results obtained were promising, with 82 of the SNOMED CT concepts correctly linked to VCM icons according to the experts. Most of the errors were easy to fix.
Year
DOI
Venue
2013
10.3233/978-1-61499-289-9-42
Studies in Health Technology and Informatics
Keywords
DocType
Volume
Terminology as Topic,SNOMED CT,Computer Graphics,Nonverbal Communication
Conference
192
ISSN
Citations 
PageRank 
0926-9630
4
0.51
References 
Authors
12
4
Name
Order
Citations
PageRank
Jean-Baptiste Lamy115427.28
Rosy Tsopra2117.71
Alain Venot311718.39
Catherine Duclos48715.08