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.

Abstract: A method and system for predicting the likelihood that a patient will suffer from atrial fibrillation is provided. The method includes receiving electrocardiogram data associated with the patient, providing at least a portion of the electrocardiogram data to a trained model, receiving a risk score indicative of the likelihood the patient will suffer from atrial fibrillation within a predetermined period of time from when the electrocardiogram data was generated, and outputting the risk score to at least one of a memory or a display for viewing by a medical practitioner or healthcare administrator. The system includes at least one processor executing instructions to carry out the steps of the method.