AI-guided screening detects new cases of atrial fibrillation, aims to prevent stroke
In a recent study, Mayo Clinic researchers used a targeted strategy to apply artificial intelligence (AI) algorithms to electrocardiogram (ECG) data to screen patients for atrial fibrillation. In the digital decentralized study, AI identified new cases of atrial fibrillation that would not have been detected in routine clinical care.
The participating patients wore a continuous ambulatory heart rhythm monitor that transmitted their heart data to the Mayo Clinic team in real time. The study found that the use of AI identified a subgroup of high-risk patients who could benefit from more intensive monitoring to detect atrial fibrillation. Doctors hope this approach can help in resource-limited environments, with the goal of connecting more patients to treatment to prevent strokes.