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The power and limits of a rule-based morpho-semantic parser.

R H Baud1, A M Rassinoux, P Ruch

  • 1Medical Informatics Division, University Hospital of Geneva, Switzerland.

Proceedings. AMIA Symposium
|November 24, 1999
PubMed
Summary

This study introduces an easy-to-use parser for analyzing medical texts from Electronic Patient Records (EPR). The tool facilitates applications like knowledge representation and intelligent medical systems.

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Area of Science:

  • Medical Informatics
  • Natural Language Processing

Background:

  • The increasing volume of digital medical texts in Electronic Patient Records (EPR) necessitates advanced text analysis tools.
  • Current applications of medical text analysis include indexing, knowledge representation, translation, and inferencing for intelligent medical systems.

Purpose of the Study:

  • To present an accessible and adaptable parser for medical text analysis.
  • To detail the capabilities and limitations of the developed parser.

Main Methods:

  • Development of a user-friendly parser for medical text processing.
  • Adaptation of the parser for diverse settings.
  • Evaluation of the parser's performance and practical constraints.

Main Results:

  • An easy-to-use parser for medical text analysis has been developed.
  • The parser demonstrates utility in various applications stemming from EPR data.
  • The study outlines the practical limitations encountered during development and application.

Conclusions:

  • The developed parser offers a practical solution for leveraging the information within Electronic Patient Records.
  • Further development and adaptation are possible for enhanced medical text analysis capabilities.