Expanding a radiology lexicon using contextual patterns in radiology reports.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jun 1, 2018

Abstract

OBJECTIVE: Distributional semantics algorithms, which learn vector space representations of words and phrases from large corpora, identify related terms based on contextual usage patterns. We hypothesize that distributional semantics can speed up lexicon expansion in a clinical domain, radiology, by unearthing synonyms from the corpus.

Authors

  • Bethany Percha
    Program in Biomedical Informatics, Stanford University, Stanford, California, USA.
  • Yuhao Zhang
    Biomedical Informatics Training Program, Stanford University, Stanford, CA, USA.
  • Selen Bozkurt
    Department of Biostatistics and Medical Informatics, Akdeniz University Faculty of Medinice, 48000 Antalya, Turkey.
  • Daniel Rubin
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Russ B Altman
    Departments of Medicine, Genetics and Bioengineering, Stanford University, Stanford, California, United States of America.
  • Curtis P Langlotz
    Stanford University, University Medical Line, Stanford, CA, 94305, US.

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