Velupillai, S;
Hadlaczky, G;
Baca-Garcia, E;
Gorrell, GM;
Werbeloff, N;
Nguyen, D;
Patel, R;
... Dutta, R; + view all
(2019)
Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior.
Frontiers in Psychiatry
, 10
, Article 36. 10.3389/fpsyt.2019.00036.
Preview |
Text
dUTTA_fpsyt-10-00036.pdf - Published Version Download (643kB) | Preview |
Abstract
Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity formental health services globally. In the last 50 years a large number of tools have been designed for suicide risk assessment, and tested in a wide variety of populations, but studies show that these tools suffer fromlow positive predictive values.More recently, advances in research fields such as machine learning and natural language processing applied on large datasets have shown promising results for health care, and may enable an important shift in advancing precision medicine. In this conceptual review, we discuss established risk assessment tools and examples of novel data-driven approaches that have been used for identification of suicidal behavior and risk. We provide a perspective on the strengths and weaknesses of these applications to mental health-related data, and suggest research directions to enable improvement in clinical practice.
| Type: | Article |
|---|---|
| Title: | Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fpsyt.2019.00036 |
| Publisher version: | https://doi.org/10.3389/fpsyt.2019.00036 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Psychiatry, suicide risk prediction, suicidality, suicide risk assessment, clinical informatics, machine learning, natural language processing, MENTAL-HEALTH RESEARCH, BIG DATA, DATA SCIENCE, CARE, HOSPITALIZATION, OPPORTUNITIES, METAANALYSIS, RECORDS, POLICY, TIME |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10076793 |
Archive Staff Only
 |
View Item |
