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.

MIT Technology Review
MIT Technology Review
3 min readOct 31, 2017

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BSIP/UIG Via Getty Images

By Jackie Snow

A new machine-learning technique documented in a paper published today in Nature Human Behaviour 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”). The researchers also used previously mapped neural signatures that show the brain patterns of emotions like “shame” and “anger.”

Five brain locations, along with six of the words, were found to be the best markers to distinguish the suicidal patients from the controls. Using just those locations and words, the researchers trained a machine-learning classifier that was able to correctly identify 15 of the 17 suicidal patients and 16 of 17 control subjects.

The researchers then divided the suicidal patients into two groups, one that had attempted suicide (nine people) and those that had not (eight people) and trained a new classifier that was able to correctly identify 16 of the 17 patients.

The results showed that healthy patients and those with suicidal thoughts showed markedly different reactions to words. For example, when the suicidal participants were shown the word “death,” the “shame” area of their brain lit up more than it did in the control group. Likewise, “trouble” also evoked more activity in the “sadness” area.

This is the just latest effort aimed at bringing AI into psychiatry. Researchers are working on machine-learning projects that span from analyzing MRIs to predict major depressive disorder to picking out PTSD from people’s speech patterns. Earlier this year, Wired wrote about researchers…

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MIT Technology Review
MIT Technology Review

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