A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data.

Journal: International journal of medical informatics
Published Date:

Abstract

OBJECTIVE: In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT).

Authors

  • Caitlin Dreisbach
    University of Virginia, School of Nursing, Charlottesville, VA, USA; University of Virginia, Data Science Institute, Charlottesville, VA, USA.
  • Theresa A Koleck
    Columbia University, School of Nursing, New York, NY, USA.
  • Philip E Bourne
    University of Virginia, Data Science Institute, Charlottesville, VA, USA; University of Virginia, Department of Biomedical Engineering, Charlottesville, VA, USA.
  • Suzanne Bakken
    Columbia University, School of Nursing, New York, NY, USA; Columbia University, Department of Biomedical Informatics, New York, NY, USA; Columbia University, Data Science Institute, New York, NY, USA. Electronic address: sbh22@cumc.columbia.edu.