Ascertainment of asthma prognosis using natural language processing from electronic medical records.

Journal: The Journal of allergy and clinical immunology
Published Date: Feb 10, 2018

Abstract

NLP algorithm successfully determined asthma prognosis (i.e., no remission, long-term remission, and intermittent remission) by taking into account asthma symptoms documented in EMR, and addressed the limitations of billing code- based asthma outcome assessment.

Authors

  • Sunghwan Sohn
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
  • Chung-Il Wi
    Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minn; Asthma Epidemiology Research Unit, Mayo Clinic, Rochester, Minn.
  • Stephen T Wu
    Oregon Health & Science University, Portland, Ore.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Euijung Ryu
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA.
  • Elizabeth Krusemark
    Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minn; Asthma Epidemiology Research Unit, Mayo Clinic, Rochester, Minn.
  • Alicia Seabright
    2 Asthma Epidemiology Research Unit.
  • Gretchen A Voge
    Department of Pediatric and Adolescent Medicine, Mayo Clinic, 200 1st Street SW, Rochester, MN, 55905, USA.
  • Young J Juhn
    Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minn; Asthma Epidemiology Research Unit, Mayo Clinic, Rochester, Minn. Electronic address: Juhn.young@mayo.edu.

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