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Sci Tech Daily on 11/2/2022
Future suicide prevention efforts could be improved by artificial intelligence.
The loss of any life is devastating, but the loss of life due to suicide is exceptionally saddening.
Suicide is the primary cause of mortality for Australians aged 15 to 44, taking the lives of almost nine people daily. According to some estimates, suicide attempts happen up to 30 times more often than fatalities.
“Suicide has large effects when it happens. It impacts many people and has far-reaching consequences for family, friends, and communities,” says Karen Kusuma, a University of New South Wales Ph.D. candidate in psychiatry at the Black Dog Institute, who investigates suicide prevention in adolescents.
Recent research conducted by Ms. Kusuma and a group of scientists from the Black Dog Institute and the Centre for Big Data Research in Health investigated the evidence supporting machine learning models’ ability to predict potential suicidal behaviors and thoughts. They evaluated the efficacy of 54 machine learning algorithms that were previously created by researchers to predict suicide-related outcomes of ideation, attempt, and death.
The meta-analysis, published in the Journal of Psychiatric Research, found that machine learning models outperformed conventional risk prediction models in predicting suicide-related outcomes, which had traditionally performed poorly.