Two graduate students from Western University have developed a ground-breaking method for predicting which intensive care unit (ICU) patients will survive a severe brain injury.
Matthew Kolisnyk and Karnig Kazazian are Ph.D. candidates at the Schulich School of Medicine and Dentistry in the lab of neuroscientist Adrian Owen.
“For years we’ve lacked the tools and techniques to know who is going to survive a serious brain injury,” said Owen.
Collaborating with neurologists at the London Health Sciences Centre and Lawson Health Research Institute, Kolisnyk and Kazazian sought to find a solution to this problem.
They were led by Loretta Norton, a psychology professor at King’s University College, who was one of the first researchers in the world to measure brain activity in the ICU.
The team measured brain activity in 25 patients in the first few days after a serious brain injury and tested whether it could predict who would survive and who would not.
A breakthrough occurred when the team combined the functional magnetic resonance imaging (fMRI) technique with an AI application known as machine learning. They found they could predict patients who would recover with an accuracy of 80 per cent, which is higher than the current standard of care.
“Modern artificial intelligence has shown incredible predictive capabilities. Combining this with our existing imaging techniques was enough to better predict who will recover from their injuries,” said Kolisnyk.
While encouraging, the researchers say the prediction was not perfect and needs further research and testing.