Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior

Velupillai, S, Hadlaczky, G.., Baca-Garcia, E. et al. (8 more authors) (2019) Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior. Frontiers in Psychiatry, 10. 36. ISSN 1664-0640

Abstract

Metadata

Authors/Creators:
  • Velupillai, S
  • Hadlaczky, G..
  • Baca-Garcia, E.
  • Gorrell, G.M.
  • Werbeloff, N.
  • Nguyen, D.
  • Patel, R.
  • Leightley, D.
  • Downs, J.
  • Hotopf, M.
  • Dutta, R.
Copyright, Publisher and Additional Information: © 2019 Velupillai, Hadlaczky, Baca-Garcia, Gorrell, Werbeloff, Nguyen, Patel, Leightley, Downs, Hotopf and Dutta. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. https://creativecommons.org/licenses/by/4.0/
Keywords: suicide risk prediction; suicidality; suicide risk assessment; clinical informatics; machine learning; natural language processing
Dates:
  • Accepted: 21 January 2019
  • Published: 13 February 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 08 Apr 2019 14:15
Last Modified: 10 Apr 2019 01:08
Status: Published
Publisher: Frontiers Media
Refereed: Yes
Identification Number: https://doi.org/10.3389/fpsyt.2019.00036
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