Automatic mining of symptom severity from psychiatric evaluation notes.

Journal: International journal of methods in psychiatric research
Published Date: Dec 22, 2017

Abstract

OBJECTIVES: As electronic mental health records become more widely available, several approaches have been suggested to automatically extract information from free-text narrative aiming to support epidemiological research and clinical decision-making. In this paper, we explore extraction of explicit mentions of symptom severity from initial psychiatric evaluation records. We use the data provided by the 2016 CEGS N-GRID NLP shared task Track 2, which contains 541 records manually annotated for symptom severity according to the Research Domain Criteria.

Authors

  • George Karystianis
    Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
  • Alejo J Nevado
    Department of Psychiatry, University of Oxford, Oxford, UK.
  • Chi-Hun Kim
    Department of Psychiatry, University of Oxford, Oxford, UK.
  • Azad Dehghan
    The Christie NHS Foundation Trust, Manchester, UK.
  • John A Keane
    School of Computer Science, University of Manchester, Manchester, UK.
  • Goran Nenadic
    School of Computer Science, University of Manchester, Manchester, UK.

Keywords

External Resources

Popular Topics
Recent Journals