Artificial Intelligence–Enabled ECG may help Detect Aortic Stenosis, Finds Study

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Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. Therefore, researchers of the Mayo Clinic, USA, developed an AI-ECG using a convolutional neural network to identify patients with moderate to severe AS. It was a retrospective study in which researchers identified 258 607 adults [mean age 63 16.3 years; women 122 790 (48%)] with echocardiography and an ECG performed within 180 days using the Mayo Clinic Unified Data Platform (UDP). The researchers tested the use of an AI-ECG to help identify patients with moderate to severe aortic stenosis (AS). Using echocardiography data, the researchers identified moderate to severe AS in 9723 (3.7%) patients. They performed Artificial intelligence training in 129 788 (50%), validation in 25 893 (10%), and testing in 102 926 (40%) in randomly selected subjects.

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