S21-047 Self-Supervised Learning of Electrocardiogram (ECG) Signals Stanford researchers have developed a contrastive learning approach that can significantly reduce the amount of labeled electrocardiogram (ECG) data required for downstream healthcare tasks, such as arrhythmia identification. Bryan Gopal Ryan Han Gautham Raghupathi Pranav Rajpurkar