UPMC, Pitt Develop Machine Learning Model to Predict Brain Injury Outcomes
Scientists from UPMC and Pitt developed a prognostic model that can accurately predict survival and recovery outcomes six months after a traumatic brain injury.
- According to researchers from UPMC and the University of Pittsburgh School of Medicine, advanced machine learning can be used to predict outcomes in patients with severe traumatic brain injuries (TBI).
In a study published in Radiology, the researchers created a deep learning model that analyzes admission CT scans and clinical data from TBI patients to predict six-month mortality and other unfavorable outcomes. The researchers noted that it typically takes two weeks for patients with severe TBI to emerge from a coma, but these patients are often taken off life support within 72 hours after hospital admission.
“Every day, in hospitals across the United States, care is withdrawn from patients who would have otherwise returned to independent living,” said co-senior author David Okonkwo, MD, PhD, professor of neurological surgery at Pitt and UPMC, in the press release. “The majority of people who survive a critical period in an acute care setting make a meaningful recovery—which further underscores the need to identify patients who are more likely to recover.”
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