A system and method for declaring arrhythmias in cardiac activity are provided. The system includes memory to store specific executable instructions and a machine learning (ML) model. One or more processors are configured to execute the specific executable instructions to obtain device classified arrhythmia (DCA) data sets generated by an implantable medical device (IMD) for corresponding candidate arrhythmias episodes declared by the IMD. The DCA data sets include cardiac activity (CA) signals for one or more beats sensed by the IMD and one or more device documented (DD) markers that are generated by the IMD. The system applies the ML model to the DCA data sets to identify a valid sub-set of the DCA data sets that correctly characterize the corresponding CA signals and to identify an invalid sub-set of the DCA data sets that incorrectly characterize the corresponding CA signals. The system includes a display configured to present information concerning at least one of the valid sub-set or invalid sub-set of the DCA data sets.
METHODS AND SYSTEMS TO CONFIRM DEVICE CLASSIFIED ARRHYTHMIAS UTILIZING MACHINE LEARNING MODELS