A deep learning approach to identify missing is-a relations in SNOMED CT.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Feb 16, 2023

Abstract

OBJECTIVE: SNOMED CT is the largest clinical terminology worldwide. Quality assurance of SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge to various SNOMED CT-based applications. In this work, we introduce a deep learning-based approach to uncover missing is-a relations in SNOMED CT.

Authors

  • Rashmie Abeysinghe
    Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Fengbo Zheng
    Department of Computer Science, University of Kentucky, Lexington, Kentucky, USA.
  • Elmer V Bernstam
    Center for Computational Biomedicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA, Department of Public Health Science, Medical University of South Carolina, 135 Cannon Street, Suite 303, Charleston, SC 29425, USA and Department of Investigational Cancer Therapeutics, Institute for Personalized Cancer Therapy, UT-MD Anderson Cancer Center, 1400 Holcombe Blvd., FC8.3044, Houston, TX 77030, USA.
  • Jay Shi
    Department of Internal Medicine, University of Kentucky, Lexington, KY, USA.
  • Olivier Bodenreider
    National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
  • Licong Cui
    The University of Texas Health Science Center at Houston, USA.

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