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Article published In:
Computational terminology and filtering of terminological information
Edited by Patrick Drouin, Natalia Grabar, Thierry Hamon, Kyo Kageura and Koichi Takeuchi
[Terminology 24:1] 2018
► pp. 91–121

HYPHEN

A flexible, hybrid method to map phenotype concept mentions to terminological resources

| University of Manchester
| University of Manchester
Narrative clinical records and biomedical articles constitute rich sources of information about phenotypes, i.e., markers distinguishing individuals with specific medical conditions from the general population. Phenotypes help clinicians to provide personalised treatments. However, locating information about them within huge document repositories is difficult, since each phenotypic concept can be mentioned in many ways. Normalisation methods automatically map divergent phrases to unique concepts in domain-specific terminologies, to allow location and linking of all mentions of a concept of interest. We have developed a hybrid normalisation method (HYPHEN) to handle concept mentions with wide ranging characteristics, across different text types. HYPHEN integrates various normalisation techniques that handle surface-level variations (e.g., differences in word order, word forms or acronyms/abbreviations) and lexical-level variations (where terms have similar meanings, but potentially unrelated forms). HYPHEN achieves robust performance for both biomedical academic text and narrative clinical records, and has the ability to significantly outperform related methods.
Keywords: normalisation, term variation, phenotypic information, terminological resources
Article outline
  • 1.Introduction
  • 2.Related work
  • 3.Methods
    • 3.1Lexical variant generation
      • 3.1.1Transformation between English and Neoclassical terminology
      • 3.1.2Synonym searching
    • 3.2Syntactic normalisation
    • 3.3Acronym and abbreviation disambiguation
    • 3.4Plural to singular
    • 3.5Hybrid methods
  • 4.Results
    • 4.1Evaluation metrics
    • 4.2Baseline and individual methods
    • 4.3Hybrid methods
    • 4.4Discussion
    • 4.5Comparison with other methods
  • 5.Conclusions and future work
  • Acknowledgements
  • Notes
  • References
Published online: 31 May 2018
DOI logo
https://doi.org/10.1075/term.00015.tho
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