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Identification of missing concepts in biomedical terminologies using sequence-based formal concept analysis.

Fengbo Zheng1,2, Rashmie Abeysinghe3, Licong Cui4

  • 1Department of Computer Science, University of Kentucky, Lexington, KY, USA.

BMC Medical Informatics and Decision Making
|November 10, 2021
PubMed
Summary

A new sequence-based Formal Concept Analysis (FCA) method effectively identifies missing concepts in biomedical terminologies like NCI Thesaurus and SNOMED CT, aiding concept naming and positioning.

Keywords:
Concept enrichmentFormal concept analysisNCI ThesaurusQuality assuranceSNOMED CT

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Area of Science:

  • Biomedical Informatics
  • Computational Linguistics
  • Knowledge Representation

Background:

  • Biomedical knowledge is rapidly expanding, necessitating the automatic identification of new concepts in terminologies.
  • Previous lexical-based Formal Concept Analysis (FCA) approaches could not handle concept naming and positioning.
  • This study introduces a novel sequence-based FCA approach for concept enrichment.

Purpose of the Study:

  • To develop and evaluate a sequence-based Formal Concept Analysis (FCA) approach for identifying potentially missing concepts in biomedical terminologies.
  • To enable automatic concept naming and positioning within existing hierarchies.
  • To validate the identified concepts using external resources.

Main Methods:

  • Concept name sequences were used as attributes to construct a formal context for FCA.
  • The longest common substrings of concept name sequences were computed for concept formation.
  • Potential positions of new concepts were predicted by identifying supertypes and subtypes.
  • Validation was performed using the Unified Medical Language System (UMLS) and PubMed.

Main Results:

  • The approach identified 1397 potentially missing concepts in the National Cancer Institute (NCI) Thesaurus and 7223 in SNOMED CT.
  • For NCI Thesaurus, 85 concepts were found in external terminologies and 315 appeared in biomedical literature.
  • For SNOMED CT, 576 concepts were found in external terminologies and 1159 appeared in biomedical literature.

Conclusions:

  • The sequence-based FCA approach demonstrates significant promise for identifying missing concepts in biomedical terminologies.
  • This method enhances the completeness and structure of biomedical knowledge bases.
  • The approach facilitates the integration of newly identified concepts into existing terminological frameworks.