A deep learning approach for medication disposition and corresponding attributes extraction.

Journal: Journal of biomedical informatics
Published Date: May 15, 2023

Abstract

OBJECTIVE: This article summarizes our approach to extracting medication and corresponding attributes from clinical notes, which is the focus of track 1 of the 2022 National Natural Language Processing (NLP) Clinical Challenges(n2c2) shared task.

Authors

  • Qiwei Gan
    VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA.
  • Mengke Hu
    Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States.
  • Kelly S Peterson
    University of Utah, Salt Lake City, UT, USA.
  • Hannah Eyre
    VA Salt Lake City Health Care System.
  • Patrick R Alba
    VA Salt Lake City Health Care System.
  • Annie E Bowles
    VA Salt Lake City Health Care System, 500, Foothill Boulevard, Salt Lake City 84148, USA; Division of Epidemiology, University of Utah, 295 Chipeta Way, Salt Lake City 84132, USA.
  • Johnathan C Stanley
    Department of Chemistry and Biochemistry, Brigham Young University Provo Utah 84602 USA dhe@chem.byu.edu.
  • Scott L DuVall
    VA Salt Lake City Health Care System.
  • Jianlin Shi
    University of Utah, Salt Lake City, UT, USA.

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