Suicides often surprise their intimates. Contrary to what one might think, a high percentage of people who decide to commit suicide do not show signs that they are going to do so, nor do they proclaim it.
Hence the importance of the method developed by researchers at Carnegie Mellon University and the University of Pittsburgh, who have combined brain imaging techniques and Artificial Intelligence algorithms to discern which individuals are suicidal, with a staggering 94 percent accuracy. The authors of the work, published in Nature, hope their finding will help save lives.
The algorithm that anticipates disaster
Scientists from these two US institutions have discovered that the neuronal activity of those who are at risk of killing themselves is different from that of other people. How did they find out?
They analyzed 34 subjects. 17 who had had suicidal thoughts at some point (nine of these had tried to kill themselves) and 17 who had no mental health problems. Each individual’s brain was scanned as they were presented with a list of ten words related to death, ten related to positive concepts – such as “carefree,” for example – and ten related to negative feelings, such as “trouble.”
They then applied a machine learning algorithm – a method that allows computers to learn on the fly – to six specific concepts: death, cruelty, problem, carefree, good, and praise. Based on the type of neural activity that these words triggered in each person, the Artificial Intelligence software detected with 91 percent accuracy whether or not the subject in question belonged to the group of possible suicides. Most surprisingly, the program identified the nine individuals in the sample who had gone to the extreme of attempting to kill themselves in the past, and did so with 94 percent accuracy.
Vital prevention
“Our research is unique because it identifies brain alterations associated with ideas of suicide. Machine learning algorithms help us create a neural representation of specific concepts related to suicide. This opens a window to the brain and mind and throws light on the way people with this problem think about suicide and the concepts related to this emotion, “says David Brent, professor of psychiatry, pediatrics and epidemiology at the University of Pittsburgh.
“The next thing – he adds – will be to apply this method to a much larger sample of people and use it to prevent suicide attempts. It must be remembered that, often, people at risk of killing themselves have detectable thought disturbances with this technique” .
Lethal statistic
To get an idea of the potential importance of this finding, it is enough to cite information from the Fundación Salud Mental España: “Suicide is the main cause of unnatural death in Spain, producing more than twice the number of deaths than traffic accidents, 7 times more than work-related accidents and 70 times more than gender-based violence, also being the leading absolute cause of death among men between 20 and 34 years of age and the second, after tumors, in both sexes of those ages.
Although the highest number of suicides in both sexes occurs between the ages of 40 and 49, the risk of suicide increases with age, especially in men, where it multiplies by 5 with respect to the earliest ages ”.
