Machine learning, imaging combine to predict those at risk of suicide
Psychology and mental health professionals may now be able to decipher distinctive patterns of activity in an individuals' brain correlated to suicide through using imaging and computer learning.
According to a recent article by NPR, a small study published in Nature Human Behaviour explored how words such as "death" and "trouble" produce a certain neurological pattern in those who are more inclined to contemplate suicide as detected through computer programming.
The study involved 34 individuals whose brains were scanned to track the activity patterns. Ultimately, the computer program was able to determine which people had thought about suicide. It was also capable of distinguishing between those who had attempted suicide from people who have only thought about it.
"We're very bad at identifying which people who are presenting with risk are in fact going to go on and have a suicide attempt," said Lisa Pan, MD, author of the study and assistant professor of psychiatry at the University of Pittsburgh School of Medicine.
The study suggests that brain scans might someday help mental health professionals prevent suicides.
For more information on the study reflections from professionals, see the full article here.
A recent graduate from Dominican University (IL) with a bachelor’s in journalism, Melissa joined TriMed’s Chicago team in 2017 covering all aspects of health imaging. She’s a fan of singing and playing guitar, elephants, a good cup of tea, and her golden retriever Cooper.