Over the last four years, Professor Min Chen has been working on an algorithm that could transform the medical field — one that could quickly diagnose strokes.
“It’s more like human and machine collaboration,” said Chen, a professor at Florida International University's College of Business.
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The algorithm uses hospital data and social determinants of health data to diagnose a stroke before lab results or diagnostic images are available.
“It’s going to predict whether the patient is at high risk or not based on a machine learning algorithm, and then if it’s high risk, it generates a popup to the care team at the emergency department,” Chen said.
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Chen said the algorithm has about 84% accuracy in diagnosing a stroke.
After reading Chen’s study published in a journal, Dr. Paulo Chaves contacted the researcher in hopes of collaboration.
“We know stroke can be a very devastating disease. While effective treatments do exist they are particularly effective if they are implemented rapidly in a few hours,” said Dr. Chaves, the director of the FIU Benjamin Leon Family Center for Geriatric Research & Education.
Health
Right now this machine-learning technology is undergoing pilot testing in the ERs of a few healthcare systems, but Dr. Chaves hopes to see the algorithm implemented locally too.
“Preventing what can be preventable, that would be fantastic!” he said.
The algorithm is in the beginning stages. More research and implementation will be key.
