Methods and systems to configure and use neural networks in characterizing physiological systems

A system comprising:

• an acquisition device configured to acquire a biophysical signal data set of a subject acquired from one or more channels of one or more sensors;
• and
• an assessment system coupled, directly or indirectly, to said device, the assessment system comprising:
• one or more processors;
• and
• a memory having instructions stored thereon, wherein execution of the instruction by the one or more processors cause the one or more processors to:
• receive the biophysical signal data set from the acquisition device;
• pre-process the biophysical signal data set to generate one or more pre-processed data sets, wherein each pre-processed data set includes a single isolated complete cardiac cycle;
• and
• determine a value indicative of presence of coronary artery disease by directly inputting the pre-processed data set to one or more deep neural networks trained with a set of training biophysical signal data set acquired from patients diagnosed with the coronary artery disease and labeled with the presence or non-presence of the coronary artery disease,
• wherein the set of training biophysical signal data set is configured as a coronary-artery- disease localization array, and wherein the localization array comprises a plurality of elements each corresponding to a label indicative of presence or non-presence of the coronary artery disease at a given location in the coronary artery, and
• wherein an output data set is outputted via a report and/or a display based on the determined value indicative of the presence of cardiac disease or condition.