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Medical language processing: applications to patient data representation and automatic encoding

N Sager1, M Lyman, N T Nhàn

  • 1Courant Institute of Mathematical Sciences, New York University, New York, USA.

Methods of Information in Medicine
|March 1, 1995
PubMed
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This study introduces a linguistic approach to represent patient data from clinical notes. The system converts narrative information into database tables and maps it to SNOMED International codes.

Area of Science:

  • Natural Language Processing
  • Medical Informatics
  • Computational Linguistics

Background:

  • Manual data extraction from clinical narratives is time-consuming.
  • Standardizing patient data representation is crucial for electronic health records.
  • Existing methods for processing clinical text have limitations.

Purpose of the Study:

  • To develop a linguistic approach for patient data representation.
  • To convert narrative clinical reports into structured database tables.
  • To map extracted data to SNOMED International codes.

Main Methods:

  • Utilizing semantic categories for computer processing of clinical reports.
  • Employing the Linguistic String Project (LSP) medical language processing (MLP) system.

Related Experiment Videos

  • Developing a procedure for mapping LSP MLP output to SNOMED International codes.

    • Main Results:

    • Demonstrated similarity between developed semantic categories and manually identified Medical Concepts.
    • Successfully converted narrative patient information into relational database tables.
    • Established a procedure for SNOMED International code mapping.

    Conclusions:

    • The linguistic approach effectively represents patient data from clinical narratives.
    • The LSP MLP system facilitates structured data extraction and coding.
    • Further development is needed to refine the system and address requirements.