Clinical utility of automatic phenotype annotation in unstructured clinical notes: intensive care unit use.

Journal: BMJ health & care informatics
Published Date:

Abstract

OBJECTIVE: Clinical notes contain information that has not been documented elsewhere, including responses to treatment and clinical findings, which are crucial for predicting key outcomes in patients in acute care. In this study, we propose the automatic annotation of phenotypes from clinical notes as a method to capture essential information to predict outcomes in the intensive care unit (ICU). This information is complementary to typically used vital signs and laboratory test results.

Authors

  • Jingqing Zhang
    Pangaea Data Limited, London SE1 7LY, UK.
  • Luis Daniel Bolanos Trujillo
    Pangaea Data Limited, London, UK.
  • Ashwani Tanwar
    Pangaea Data Limited, London SE1 7LY, UK.
  • Julia Ive
    Pangaea Data Limited, London SE1 7LY, UK.
  • Vibhor Gupta
    American Oncology Institute, Hyderabad, CA, India.
  • Yike Guo
    Department of Computing, Imperial College, London SW7 2AZ, UK. y.guo@imperial.ac.uk.