Artificial intelligence and suicide prevention: A systematic review. Issue 1 (15th February 2022) - Lejeune, Alban; Le Glaz, Aziliz; Perron, Pierre-Antoine; Sebti, Johan; Baca-Garcia, Enrique; Walter, Michel; Lemey, Christophe; Berrouiguet, Sofian
Abstract: 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.