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Artificial intelligence and suicide prevention: A systematic review
BACKGROUND: Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide. METHODS: A systematic review...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988272/ https://www.ncbi.nlm.nih.gov/pubmed/35166203 http://dx.doi.org/10.1192/j.eurpsy.2022.8 |
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author | Lejeune, Alban Le Glaz, Aziliz Perron, Pierre-Antoine Sebti, Johan Baca-Garcia, Enrique Walter, Michel Lemey, Christophe Berrouiguet, Sofian |
author_facet | Lejeune, Alban Le Glaz, Aziliz Perron, Pierre-Antoine Sebti, Johan Baca-Garcia, Enrique Walter, Michel Lemey, Christophe Berrouiguet, Sofian |
author_sort | Lejeune, Alban |
collection | PubMed |
description | BACKGROUND: Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide. METHODS: A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords. RESULTS: Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings. CONCLUSIONS: AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified. |
format | Online Article Text |
id | pubmed-8988272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-89882722022-04-15 Artificial intelligence and suicide prevention: A systematic review Lejeune, Alban Le Glaz, Aziliz Perron, Pierre-Antoine Sebti, Johan Baca-Garcia, Enrique Walter, Michel Lemey, Christophe Berrouiguet, Sofian Eur Psychiatry Review/Meta-analysis BACKGROUND: Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide. METHODS: A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords. RESULTS: Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings. CONCLUSIONS: AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified. Cambridge University Press 2022-02-15 /pmc/articles/PMC8988272/ /pubmed/35166203 http://dx.doi.org/10.1192/j.eurpsy.2022.8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Review/Meta-analysis Lejeune, Alban Le Glaz, Aziliz Perron, Pierre-Antoine Sebti, Johan Baca-Garcia, Enrique Walter, Michel Lemey, Christophe Berrouiguet, Sofian Artificial intelligence and suicide prevention: A systematic review |
title | Artificial intelligence and suicide prevention: A systematic review |
title_full | Artificial intelligence and suicide prevention: A systematic review |
title_fullStr | Artificial intelligence and suicide prevention: A systematic review |
title_full_unstemmed | Artificial intelligence and suicide prevention: A systematic review |
title_short | Artificial intelligence and suicide prevention: A systematic review |
title_sort | artificial intelligence and suicide prevention: a systematic review |
topic | Review/Meta-analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8988272/ https://www.ncbi.nlm.nih.gov/pubmed/35166203 http://dx.doi.org/10.1192/j.eurpsy.2022.8 |
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