Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing.

Abstract

Authors

• Jihye Kim Scroggins
  Columbia University School of Nursing, New York, New York, USA.
• Ismael I Hulchafo
  School of Nursing, Columbia University, New York, NY 10032, United States.
• Sarah Harkins
  School of Nursing, Columbia University, New York, NY, United States.
• Danielle Scharp
  Columbia University School of Nursing, New York, NY.
• Hans Moen
  Turku NLP Group, Department of Future Technologies, University of Turku, Finland.
• Anahita Davoudi
  Biostatistics, Epidemiology & Informatics, University of Pennsylvania, Philadelphia, PA.
• Kenrick Cato
  School of Nursing, Columbia University, New York City, NY, USA.
• Michele Tadiello
  Center for Community-Engaged Health Informatics and Data Science, Columbia University Irving Medical Center, New York, NY 10032, United States.
• Maxim Topaz
  Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.
• Veronica Barcelona
  School of Nursing, Columbia University, 560 West 168th St, Mail Code 6, New York, NY, 10032, USA. vb2534@cumc.columbia.edu.

Keywords

External Resources