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Representing clinical narratives using conceptual graphs

R H Baud1, A M Rassinoux, J C Wagner

  • 1Faculty of Medicine, University of Geneva, Switzerland.

Methods of Information in Medicine
|March 1, 1995
PubMed
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This study introduces a multilingual Conceptual Graphs (CG) system for analyzing medical narratives. It enables natural language understanding by focusing on semantic meaning and medical domain knowledge.

Area of Science:

  • Computational linguistics
  • Medical informatics
  • Artificial intelligence

Background:

  • Effective analysis of medical narratives requires robust representation languages capable of handling complex human reasoning.
  • Existing methods often prioritize syntax over semantics, limiting their expressiveness in specialized domains.

Purpose of the Study:

  • To present a multilingual implementation of Sowa's Conceptual Graphs (CG) for medical natural language understanding.
  • To demonstrate a semantic-dominant approach to natural language understanding (NLU) using Conceptual Graphs.

Main Methods:

  • Developed a multilingual Conceptual Graphs (CG) system supporting French, English, and German.
  • Employed Proximity Processing to aggregate words based on semantic compatibility rules.

Related Experiment Videos

  • Gradually constructed CG representations from individual words using a medical semantic lexicon and a medical Linguistic Knowledge Base.

    • Main Results:

    • Demonstrated the feasibility of a semantic-dominant approach to NLU in the medical domain.
    • Successfully generated complete CG representations of sentences from medical narratives.
    • Showcased the system's ability to handle the complexity of medical reasoning.

    Conclusions:

    • Conceptual Graphs provide an adequate and expressive representation language for medical narrative analysis.
    • A semantic-dominant approach, guided by domain-specific knowledge, is effective for medical NLU.
    • The multilingual CG implementation facilitates cross-lingual analysis of medical texts.