Abstract: A method includes the step of receiving electrocardiogram (ECG) data associated with a plurality of patients and an electrocardiogram configuration including a plurality of leads and a time interval. The electrocardiogram data includes, for each lead included in the plurality of leads, voltage data associated with at least a portion of the time interval. The method also includes training an artificial intelligence model on the ECG data, tuning the artificial intelligence model using data from a device having fewer leads than the plurality of leads, and evaluating the artificial intelligence model on additional data received from the ECG data.

Abstract: Computer-implemented systems and methods are provided for supplying electrocardiograms and identified patient information to an artificial intelligence engine comprising a neural network configured with a fractional flow reserve prediction model and that predicts a calculated fractional flow reserve for the patient, from which a predicted occurrence of one or more cardiac events is determined.