Computer scientists from Duke University and Harvard University have joined with physicians from Massachusetts General Hospital and the University of Wisconsin to develop a machine learning model that can predict which patients are most at risk of having destructive seizures after suffering a stroke or other brain injury.
A point system they’ve developed helps determine which patients should receive expensive continuous electroencephalography (cEEG) monitoring. Implemented nationwide, the authors say their model could help hospitals monitor nearly three times as many patients, saving many lives as well as $54 million each year.
A paper detailing the methods behind the interpretable machine learning approach appeared online June 19 in the Journal of Machine Learning Research.
Comments are closed.