Machine Matches Docs for Arrhythmia Detection

Posted by iRhythm Technologies on January 9, 2019

MedPage Today writes that for detecting a variety of arrhythmias, ambulatory ECG data analysis with a deep neural network (DNN) did better than cardiologists in most cases, researchers found in an experimental setting.

The DNN developed by Awni Hannun, PhD, of Stanford University in California, and colleagues, achieved an average area under the receiver-operating characteristic curve (ROC) of 0.97 when confirmed against independent test data annotated by a committee of board-certified practicing cardiologists.

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