New Software Diag**ses Cardiac Arrhytmias from ECGs Better Than Cardiologists
 

New Software Diag**ses Cardiac Arrhytmias from ECGs Better Than Cardiologists
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Stanford researchers claim to have developed an algorithm that “exceeds the performance of board certified*cardiologists in detecting a wide range of heart arrhythmias from electrocardiograms [ECG] recorded with a single-lead wearable monitor,” according to a*study published in arXiv.

The team used the Zio ***** from iRhythm Tech**logies, a San Francisco, CA startup, which allowed them to gather ECG recordings over a period of up to two weeks. These recordings were run against a computer running a deep learning algorithm that was trained by analyzing almost 30,000 previously gathered and diag**stically assessed ECG recordings. The result is that the system is **w able to spot 14 different types of cardiac arrhythmias purportedly better than the six Stanford cardiologists that were pitted against it.

Here’s a Stanford video with the researchers that developed the algorithm:



Related flashbacks:*Medgadget Exclusive Interview with iRhythm’s CEO Kevin King…;*ZIO Wireless ***** May Be Better Option Than Holter Monitors for Cardiac Arrhythmia Diag**sis…;

Study in arXiv: Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks…

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