How AI Can Predict Heart Attacks and Strokes

To try to develop a more qualitative tool, Knott and his colleagues trained an AI model to read scans and learn to detect signs of compromised blood flow. When they tested the technology on the scans of more than 1,000 people who needed CMR because they either at risk of developing heart disease or had already been diagnosed, they found the AI model worked pretty well at selecting out which people were more likely to go on to have a heart attack or stroke, or die from one.

“Rather than a qualitative view of blood flow to the heart muscle, we get a quantitative number,” he says. “And from that number, we’ve shown that we can predict which people are at higher risk of adverse events.” The study confirmed that CMR is a strong marker for risk of heart problems, but did not prove that the scans could actually be used to guide doctors’ decisions about which people are at higher risk. For that, more studies need to be done that document whether treating poor blood flow—with available medication or procedures—in people with decreased flow as predicted by the AI model, can reduce or eliminate heart attacks and strokes.

The goal is to include an AI-based analysis of blood flow as part of the tests that doctors use in the emergency room to diagnose and triage heart patients. The information could help to move the highest risk people to treatments sooner, and potentially save their lives.

Interesting read!

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