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Conceptual search in electronic patient record.

R H Baud1, C Lovis, P Ruch

  • 1Medical Informatics Division, University Hospital of Geneva, Switzerland. Robert.Baud@dim.hcuge.ch

Studies in Health Technology and Informatics
|October 18, 2001
PubMed
Summary

This study enhances medical text searching by adding a conceptual model to string matching, improving results beyond traditional GREP methods. The new system accepts natural language queries, offering better discoverability of domain-specific knowledge.

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Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Information Retrieval

Background:

  • Current content search in large medical text corpora is limited.
  • Traditional GREP (Get Regular Expression and Print) methods struggle with domain-specific knowledge and require Boolean queries.
  • Poor search results occur when Boolean query constraints are not met.

Purpose of the Study:

  • To enhance content search in medical texts.
  • To overcome limitations of traditional string matching and GREP approaches.
  • To improve the quality and accessibility of search results.

Main Methods:

  • Implemented an enhancement to string matching search.
  • Integrated a light conceptual model with the word lexicon.

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  • Utilized advanced indexing algorithms during a pre-processing phase for efficiency.

    • Main Results:

    • The new system accepts natural language sentences as queries.
    • Radically improved the quality of search results.
    • Achieved efficiency in execution time through advanced indexing.

    Conclusions:

    • The enhanced search system offers a significant improvement over existing methods.
    • The integration of a conceptual model broadens the applicability of text search in the medical domain.
    • The system provides a more effective way to retrieve domain-specific knowledge from medical texts.