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Solving a challenge: This was the first task set out by the Mount Sinai AI Consortium, a group of scientists, physicians and researchers at New York City–based Mount Sinai Health System dedicated to developing artificial intelligence in medicine.
“We wanted to [apply AI] in the healthcare context and tackle a problem that is clinically impactful and relevant to our practices,” says Eric Karl Oermann, instructor in the department of neurosurgery at the Icahn School of Medicine and director of the AI program, dubbed AISINAI.
The challenge the group landed on was to identify markers of acute neurological illnesses, such as hemorrhages and strokes. Time matters because a patient’s “clinical condition is something that worsens, in some cases, by the minute,” says Oermann. “They’re extremely time-sensitive.”
With this in mind, the group set out to see if they could find a way to use AI and deep learning to save some of those precious minutes. The attempt was a success: By leveraging the application of computer vision in the medical field, Mount Sinai’s system can now identify a problem from a CT scan in 1.2 seconds — 150 times faster than it would takes a physician to read the image.
Continue reading at healthtechmagazine.net
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