AI Has Learned to Spot Suicidal Tendencies from Brain Scans

Suicide is the second-leading cause of death among young people between the ages of 15 and 34 in the United States, and clinicians have limited tools to identify those at risk. A new machine-learning technique documented in a paper published today in Nature Human Behaviour (PDF) could help identify those suffering from suicidal thoughts. Researchers looked at 34 young adults, evenly split between suicidal participants and a control group. Each subject went through a functional magnetic resonance imaging (fMRI) and were presented with three lists of 10 words. All the words were related to suicide (words like "death," "distressed," or "fatal"), positive effects ("carefree," "kindness," "innocence"), or negative effects ("boredom," "evil," "guilty").