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

Arguello, M, Des, J, Fernandez-Prieto, MJ, Perez, R and Lekkas, S 2011, An ontology-based approach to natural language generation from coded data in electronic health records , in: 5th European Symposium on Computer Modeling and Simulation, 16th - 18th November 2011, Madrid, Spain.

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    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.

    Item Type: Conference or Workshop Item (Paper)
    Themes: Subjects outside of the University Themes
    Schools: Colleges and Schools > College of Arts & Social Sciences > School of Humanities, Languages & Social Sciences > Centre for Translating and Interpreting
    Journal or Publication Title: Proceedings of the 5th European Symposium on Computer Modeling and Simulation
    Publisher: IEEE
    Refereed: Yes
    Depositing User: Users 29196 not found.
    Date Deposited: 13 Dec 2011 16:56
    Last Modified: 20 Aug 2013 18:19
    URI: http://usir.salford.ac.uk/id/eprint/19176

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