A method for the machine generation of a model for predicting patient outcome following the occurrence of an event. In one embodiment the method includes the steps of obtaining a physiological signal of interest, the physiological signal having a characteristic obtaining a time series of a signal characteristic 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 generate a weighted risk vector.
