AI-based method predicts risk of atrial fibrillation

Atrial fibrillation -- an irregular and often rapid heart rate -- is a common condition that often leads to the formation of clots in the heart that can travel to the brain to cause a stroke. The study was published in Circulation. The investigators developed the artificial intelligence-based method to predict the risk of atrial fibrillation within the next five years based on results from electrocardiograms (noninvasive tests that record the electrical signals of the heart) in 45,770 patients receiving primary care at MGH. Next, the scientists applied their method to three large data sets from studies including a total of 83,162 individuals. The AI-based method predicted atrial fibrillation risk on its own and was synergistic when combined with known clinical risk factors for predicting atrial fibrillation. The method was also highly predictive in subsets of individuals such as those with prior heart failure or stroke.