An ontological approach for the exploitation of clinical data.
Clinical data captured in hospital information systems may be unusable in their original format due to missing information or knowledge. The use of external resources (e.g. domain ontology) could be a way of dealing with this lack of knowledge. Our study thus aimed to develop a framework allowing a user to perform medical queries in the context of infectious diseases. By creating an interaction between a knowledge source and clinical data, using semantic and semantic web tools and methods, the users are able to perform queries on a database to obtain results about antibiotic resistance. This work has been performed in the context of the DebugIT European project that aims to control and monitor the antibioresistance growth via a semantic interoperability platform. The results obtained by the use of different semantic web tools were quantitatively evaluated by comparison of the number of results and the query execution time. We have compared our approach with classic business intelligence approaches in terms of usability and functionality.
INSERM UMR_S 872 Eq 20, Université Pierre et Marie Curie, Paris, France.
Ariane
A
Assélé Kama
Rémy
R
Choquet
Giovanni
G
Mels
Christel
C
Daniel
Jean
J
Charlet
Marie-Christine
MC
Jaulent
D064229:Biological Ontologies; D003141:Communicable Diseases / Q000145:classification*; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D005060:Europe; D006751:Hospital Information Systems; D006801:Humans; D009323:Natural Language Processing; D012660:Semantics; D009626:Terminology as Topic