Communications of the ACM
Detecting Long-Term Concussion in Athletes
A recent study at the University of Montreal in Canada helped computers using artificial intelligence software to "learn" the differences between the brain of a healthy athlete versus the brain of a previously concussed athlete.
Credit: Medscape
Researchers at the University of Montreal in Canada recently conducted a study examining the brains of athletes who had suffered concussions, and comparing them to athletes who had not suffered concussions.
The researchers collected the data and fed it to computers that use artificial intelligence software to "learn" the differences between the brain of a healthy athlete versus the brain of a previously concussed athlete.
The researchers found that white matter connections between several brain regions of concussed athletes showed abnormal connectivity that could reflect degeneration, as well as the brain's ability to compensate for damage.
The software used the data to detect concussions with up to 90% accuracy. The researchers now plan to validate the results on a larger sample size using various magnetic resonance imaging scanners, so it could eventually become an effective means to diagnose concussions.
From McGill University (Canada)
View Full Article
Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA
No entries found