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A team of scientists from Geisinger and Tempus have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke.
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DANVILLE, Pa. - A team of scientists from Geisinger and Tempus have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke.
Atrial fibrillation is the most common cardiac arrhythmia and is associated with numerous health risks, including stroke and death. The study, published in
Circulation, used electrical signals from the heart measured from a 12-lead electrocardiogram (ECG) to identify patients who are likely to develop AF, including those at risk for AF-related stroke. Each year, over 300 million ECGs are performed in the U.S. to identify cardiac abnormalities within an episode of care. However, these tests cannot generally detect future potential for negative events like atrial fibrillation or stroke, said Joel Dudley, chief scientific officer at Tempus. This critical work stems from our major investments in cardiology to generate algorithms that make existing cardiology tests, such as ECGs, smarter and capab