Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.

Journal: Rheumatology (Oxford, England)
Published Date: May 1, 2020

Abstract

OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Classification of Diseases (ICD) codes.

Authors

  • Sizheng Steven Zhao
    Institute of Ageing and Chronic Disease, University of Liverpool.
  • Chuan Hong
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Tianrun Cai
    Harvard-MIT Center for Regulatory Science, Harvard Medical School, Boston, MA, United States.
  • Chang Xu
    Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian 116089, China.
  • Jie Huang
    Department of Critical Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Joerg Ermann
    Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital.
  • Nicola J Goodson
    Institute of Ageing and Chronic Disease, University of Liverpool.
  • Daniel H Solomon
    Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital.
  • Tianxi Cai
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
  • Katherine P Liao
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States.

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