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Supporting SNOMED CT postcoordination with knowledge graph embeddings.

Javier Castell-Díaz1, Jose Antonio Miñarro-Giménez1, Catalina Martínez-Costa1

  • 1Dept. Informatica y Sistemas, Universidad de Murcia, IMIB-Arrixaca, Murcia, Spain.

Journal of Biomedical Informatics
|February 3, 2023
PubMed
Summary
This summary is machine-generated.

KGE4SCT simplifies creating SNOMED CT postcoordinated expressions using knowledge graph embeddings. This method enhances automatic clinical information extraction and encoding from text.

Keywords:
Knowledge graph embeddingsOntologyPostcoordinationSNOMED CT

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Area of Science:

  • Medical Informatics
  • Computational Linguistics
  • Knowledge Representation

Background:

  • SNOMED CT postcoordination enables defining new clinical concepts but is complex to perform manually.
  • Advanced systems for automatic clinical information extraction require effective SNOMED CT postcoordination.

Purpose of the Study:

  • To implement KGE4SCT, a method for automatically suggesting SNOMED CT postcoordinated expressions for clinical terms.
  • To leverage SNOMED CT ontology and knowledge graph embeddings (KGEs) for this task.

Main Methods:

  • Utilized SNOMED CT ontology and its graph structure.
  • Applied knowledge graph embeddings to represent entities and relations in a vector space.
  • Employed vector similarity and analogies to derive postcoordinated expressions.

Main Results:

  • Achieved 98% semantic type accuracy, 90% relationship accuracy, and 52% overall postcoordination completeness for Spanish SNOMED CT.
  • Outperformed state-of-the-art methods on English SNOMED CT for corpus generation (6% analogy accuracy improvement) and automatic postcoordination (17% partial conversion rate increase).

Conclusions:

  • KGE4SCT effectively supports the creation of SNOMED CT postcoordinated expressions.
  • The method demonstrates significant improvements in accuracy and completeness for both Spanish and English SNOMED CT versions, advancing automated clinical information processing.