An ontology-based approach to natural language generation from coded data in
electronic health records

Arguello, M; Des, J; Fernandez-Prieto, MJ; Perez, R; Lekkas, S

Abstract

The worldwide adoption of the HL7 Clinical
Document Architecture (CDA) is promoting the availability of
coded data (CDA entries) within sections of clinical documents.
At the moment, an increasing number of studies are
investigating ways to transform the narratives of CDA
documents into machine processable CDA entries. This paper
addresses the reverse problem, i.e. obtaining linguistic
representations (sentences) from CDA entries. The approach
presented employs Natural Language Generation (NLG)
techniques and deals with two major tasks: content selection
and content expression. The current research proposes a
formal semantic representation of CDA entries and
investigates how expressive domain ontologies in OWL and
SPARQL SELECT queries can contribute to NLG. To validate
the proposal, the study has focused on CDA entries from the
History of Present Illness sections of CDA consultation notes.
The results obtained are encouraging, as the clinical narratives
automatically generated from these CDA entries fulfil the
clinicians’ expectations.

Citation

electronic health records. Presented at 5th European Symposium on Computer Modeling and Simulation, Madrid, Spain

• Presentation Conference Type: Other
• Conference Name: 5th European Symposium on Computer Modeling and Simulation
• Conference Location: Madrid, Spain
• End Date: Nov 18, 2011
• Publication Date: Jan 1, 2011
• Deposit Date: Dec 13, 2011
• Publisher URL: http://www.uksim.info/ems2011/ToC.pdf
• Additional Information: Event Type : Conference