Mayo Clinic and AliveCor use AI to detect 'invisible' heart condition

Investigators from the Mayo Clinic and AliveCor demonstrated that a trained artificial intelligence network can help identify people at increased risk of arrhythmias and sudden cardiac death despite displaying a normal heart rhythm on their electrocardiogram. Up to half of patients with long QT syndrome can show a normal interval on a standard test, the personal EKG manufacturer AliveCor said in a statement. Correct diagnoses and treatment can be crucial, especially when using drugs that may prolong heartbeats. The researchers' deep neural network generated the results using data from a single lead of a 12-lead EKG--measuring the voltage between the left and right arms--suggesting that simpler, portable devices may be used to detect the concealed heart condition, the company said. The network had an overall accuracy of 79%, with 73% sensitivity and 81% specificity.