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Medical language processing with SGML display

N Sager1, N T Nhàn, M Lyman

  • 1Courant Institute of Mathematical Sciences, New York University, NY 10012, USA.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1996
PubMed
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This study integrates medical language processing with new display technologies to efficiently extract data from patient documents. These methods enable faster review through highlighted results, paving the way for advanced text analysis.

Area of Science:

  • Biomedical Informatics
  • Medical Data Science
  • Clinical Informatics

Background:

  • Free-text clinical documents contain valuable patient data.
  • Manual extraction of this data is time-consuming and prone to errors.
  • Emerging display technologies offer new avenues for data visualization and interaction.

Purpose of the Study:

  • To explore the integration of medical language processing (MLP) with advanced display technologies.
  • To demonstrate methods for efficient data extraction from unstructured clinical notes.
  • To enhance the review process of processed medical text.

Main Methods:

  • Utilized natural language processing (NLP) techniques for medical text analysis.
  • Developed methods to combine NLP outputs with visual display features.

Related Experiment Videos

  • Implemented highlighting and markup to signify extracted data points.

    • Main Results:

    • Successfully demonstrated techniques for combining MLP and display technologies.
    • Achieved rapid review of processed patient documents through visual highlighting.
    • Showcased the potential for interactive data extraction from clinical notes.

    Conclusions:

    • The integration of MLP and display technologies offers a powerful approach for clinical data extraction.
    • Visual highlighting significantly accelerates the review of processed medical text.
    • Future work can involve coupling text markup with advanced downstream analytical procedures.