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A substring replacement approach for identifying missing IS-A relations in SNOMED CT.

Xubing Hao1, Rashmie Abeysinghe2, Jay Shi3

  • 1School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|February 13, 2023
PubMed
Summary

This study introduces a novel substring replacement method to identify missing hierarchical relationships in SNOMED CT, enhancing biomedical ontology quality. The approach achieved 89% precision in expert validation, improving the accuracy of clinical terminology.

Keywords:
Ontologies and TerminologiesOntology Quality AssuranceSNOMED CTUMLS

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Area of Science:

  • Biomedical Informatics
  • Medical Terminology
  • Ontology Engineering

Background:

  • Biomedical ontologies are crucial for research and applications, but suffer from quality issues like incomplete hierarchies.
  • SNOMED CT, a widely used clinical terminology, requires continuous quality assurance, particularly for its hierarchical structure.

Purpose of the Study:

  • To develop and evaluate a method for identifying missing IS-A relations in SNOMED CT's class hierarchy.
  • To improve the completeness and accuracy of SNOMED CT through automated and manual validation techniques.

Main Methods:

  • A substring replacement approach was developed, utilizing lexical features of concepts and existing IS-A relations.
  • Automated validation employed relations from the Unified Medical Language System (UMLS).
  • Manual validation involved a domain expert reviewing 100 identified potential missing relations.

Main Results:

  • The approach identified 3,228 potential missing IS-A relations in the SNOMED CT US Edition (March 2022).
  • Automated validation confirmed 63 of these relations via UMLS.
  • Manual expert review demonstrated 89% precision, validating the approach's effectiveness.

Conclusions:

  • The substring replacement method is effective for identifying missing IS-A relations in SNOMED CT.
  • This approach contributes to the quality assurance of biomedical ontologies, specifically SNOMED CT's hierarchical integrity.