CARE-SD: classifier-based analysis for recognizing provider stigmatizing and doubt marker labels in electronic health records: model development and validation.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 39724920

Abstract

OBJECTIVE: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.

Authors

  • Andrew Walker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, United States.
  • Annie Thorne
    Department of Infectious Disease, Children's Healthcare of Atlanta, Atlanta, GA 30329, United States.
  • Sudeshna Das
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Jennifer Love
    Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
  • Hannah L F Cooper
    Emory University, Rollins School of Public Health, Department of Behavioral, Social and Health Education Sciences, Atlanta, GA, USA.
  • Melvin Livingston
    Department of Behavioral, Social, Health Education Sciences, Rollins School of Public Health, Emory University, Atlanta, GA 30322, United States.
  • Abeed Sarker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.

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