Stanford researchers developed a deep learning algorithm that can diagnose 14 types of heart rhythm abnormalities with cardiologist-level accuracy. They are able to identify irregular heartbeats, called arrhythmias, from sifting through hours of heart rhythm using electrocardiogram (ECG) signals generated by wearable monitors �C which can be used to speed diagnosis and improve treatment for people��
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