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Applying Natural Language Generation to Electronic Health Records in an e-Science context

Donia Scott ( Open University )

At the centre of the Clinical e-Science Framework (CLEF) is a repository of well organised, detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico medical experiments. This talk will present an overview of the CLEF concept, and will describe two ways in which natural language generation technologies are being employed to service the requirements of clinicians and medical researchers as users of CLEF:

  • a query editing interface, which makes use of natural language generation techniques in order to alleviate some of the problems generally faced by natural language and graphical query interfaces, thereby allowing biomedical researchers and clinicians to query -- in an intuitive way -- the repository of patient data and to receive dynamically generated multimedia responses
  • a report generator, which produces on-demand a range of medical reports on the clinical histories of individual patients, tailored to different needs (e.g., perspectives and purposes) of the clinician.

 

 

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