Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
Abstract
The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart. Here we hypothesize that a deep neural network can predict an important future clinical event (one-year all-cause mortality) from ECG voltage-time traces. We show good performance for predicting one-year mortality with an average AUC of 0.85 from a model cross-validated on 1,775,926...
Paper Details
Title
Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
Published Date
Apr 15, 2019
Journal
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