For every one of these suicide deaths, there are five people hospitalized following self-injury, 25 to 30 suicide attempts and seven to 10 people affected by each tragedy, according to analysis by the Public Health Agency of Canada.
Could artificial intelligence (AI), or intelligence demonstrated by machines, possibly help to prevent these deaths?
As researchers in psychiatry, in the Canadian Biomarker Integration Network for Depression, we are collecting clinical and biological data during treatment interventions for people with major depression. We are exploring early clues to changes in behaviour and mood states using mobile health technologies.
One of our goals is to identify early predictors of relapse, and increased risk of suicidal behaviour.
Here we review other promising applications of AI to suicide prevention, and draw attention to the barriers within this field.
AI technology has also been integrated into suicide management to improve patient care in other areas. AI assessment tools have been shown to predict short-term suicide risk and make treatment recommendations that are as good as clinicians. The tools are also well-regarded by patients.
AI models predict individual risk
Current evaluation and management of suicide risk is still highly subjective. To improve outcomes, more objective AI strategies are needed. Promising applications include suicide risk prediction and clinical management.