Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text.

Journal: Studies in health technology and informatics
Published Date: Jan 25, 2024

Abstract

Natural Language Processing can be used to identify opioid use disorder in patients from clinical text1. We annotate a corpus of clinical text for mentions of concepts associated with unhealthy use of opiates including concept modifiers such as negation, subject, uncertainty, relation to document time and illicit use.

Authors

  • Abdullateef I Almudaifer
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Sue S Feldman
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Tobias O'Leary
    University of Alabama at Birmingham, Birmingham, Alabama, USA.
  • Whitney L Covington
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • JaMor Hairston
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Zachary Deitch
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Estera Crisan
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Kevin Riggs
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Lauren Walters
    University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • John D Osborne
    Center for Clinical and Translational Science, University of Alabama at Birmingham, Birmingham, Alabama, USA, 35294 ozborn@uab.edu.

Keywords

External Resources

Popular Topics
Recent Journals