Natural language processing for structuring clinical text data on depression using UK-CRIS.

Journal: Evidence-based mental health
Published Date: Feb 1, 2020

Abstract

BACKGROUND: Utilisation of routinely collected electronic health records from secondary care offers unprecedented possibilities for medical science research but can also present difficulties. One key issue is that medical information is presented as free-form text and, therefore, requires time commitment from clinicians to manually extract salient information. Natural language processing (NLP) methods can be used to automatically extract clinically relevant information.

Authors

  • Nemanja Vaci
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK nemanja.vaci@psych.ox.ac.uk.
  • Qiang Liu
    Blood Transfusion Laboratory, Jiangxi Provincial Blood Center Nanchang 330052, Jiangxi, China.
  • Andrey Kormilitzin
    University of Oxford, United Kingdom of Great Britain and Northern Ireland. Electronic address: andrey.kormilitzin@psych.ox.ac.uk.
  • Franco De Crescenzo
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Ayse Kurtulmus
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Jade Harvey
    Research and Development, Oxford Health NHS Foundation Trust, Oxford, Oxfordshire, UK.
  • Bessie O'Dell
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Simeon Innocent
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Anneka Tomlinson
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Andrea Cipriani
    Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, UK.
  • Alejo Nevado-Holgado
    University of Oxford, United Kingdom of Great Britain and Northern Ireland. Electronic address: alejo.nevado-holgado@psych.ox.ac.uk.

Keywords

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