Abstract: Various methods and systems are provided for analyzing an electrocardiogram (ECG) in real-time using machine learning to identify heartbeats, calculate a cycle length for each heartbeat, and display the cycle length for each heartbeat at a user interface. Waveform morphology of ECG data is continuously learned to identify recurrent signals and generate templates based on recurrent signals, to which ECG data is compared to identify and display heartbeats. Generated templates are continuously updated to reflect changing waveform morphologies.