Paper Info
Title
Automatic definition of the oncologic EHR data elements from NCIT in OWL.
Abstract
Semantic interoperability based on ontologies allows systems to combine their information and process them automatically. The ability to extract meaningful fragments from ontology is a key for the ontology re-use and the construction of a subset will help to structure clinical data entries. The aim of this work is to provide a method for extracting a set of concepts for a specific domain, in order to help to define data elements of an oncologic EHR. Method: a generic extraction algorithm was developed to extract, from the NCIT and for a specific disease (i.e. prostate neoplasm), all the concepts of interest into a sub-ontology. We compared all the concepts extracted to the concepts encoded manually contained into the multi-disciplinary meeting report form (MDMRF). Results: We extracted two sub-ontologies: sub-ontology 1 by using a single key concept and sub-ontology 2 by using 5 additional keywords. The coverage of sub-ontology 2 to the MDMRF concepts was 51%. The low rate of coverage is due to the lack of definition or mis-classification of the NCIT concepts. By providing a subset of concepts focused on a particular domain, this extraction method helps at optimizing the binding process of data elements and at maintaining and enriching a domain ontology.
Year
DOI
Venue
2011
10.3233/978-1-60750-806-9-517
Studies in Health Technology and Informatics
Keywords
Field
DocType
Semantic interoperability,information system,ontology modularization,date elements,value-set
World Wide Web,Information retrieval,Computer science,Automatic transmission
Conference
Volume
ISSN
Citations 
169
0926-9630
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Marc Cuggia110120.05
Annabel Bourde2183.07
Bruno Turlin301.01
Sebastien Vincendeau400.68
Valérie Bertaud551.21
Catherine Bohec600.34
Régis Duvauferrier7214.98