variables and anatomic factors may contribute to sex and age-related differences on the
ECG. We hypothesized that a convolutional neural network (CNN) could be trained through
a process called deep learning to predict a person's age and self-reported sex using only 12-
lead ECG signals. We further hypothesized that discrepancies between CNN-predicted age
and chronological age may serve as a physiological measure of health. Methods: We …