1. A method for the machine generation of a model for predicting death within a predetermined period following the occurrence of a cardiac event, the method comprising the steps of: obtaining an ECG of interest from a plurality of patients having a plurality of outcomes, the ECG having a plurality of ECG characteristics; obtaining a time series of one of the ECG characteristics of the plurality of ECG characteristics; dividing the time series into a plurality of window segments; converting the time series from time-space to beat-space; computing the power in various frequency bands of each window segment; computing the 90th percentile of the spectral energies across all window segments for each frequency band; and inputting the data into a machine learning program to obtain a weighted risk vector.