Towards a comprehensive medical language processing system: methods and issues

  • Friedman C
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Abstract

Natural language processing (NLP) systems can help solve the data entry problem by providing coded data from textual reports for clinical applications. A number of NLP systems have shown promise, but have not yet achieved wide-spread use for practical applications. In order to achieve such use, a system must have broad coverage of the clinical domain and not be restricted to limited applications. In addition, an NLP system must perform satisfactorily for real-world applications. This paper describes methods and issues associated with an ongoing extension of MedLEE, an operational NLP system, from a limited domain to a domain that encompasses comprehensive clinical information.

Author-supplied keywords

  • *Natural Language Processing
  • *Radiology Information Systems
  • Humans
  • Medical Records Systems, Computerized
  • Patient Discharge
  • Radiography, Thoracic/classification

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Authors

  • C Friedman

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