In the study, 6,158 participants used the Apple Watch and the Cardiogram app to measure their heart rate.
When combined with an artificial-intelligence based algorithm, atrial fibrillation – a common abnormal heart rhythm – can be detected with a staggering 97 percent accuracy.
Since the study was launched in March 2016, more than 30 billion data points have already been collected by the app.
While the accuracy rate is definitely notable, it will take some time before the app itself can possibly warn users of an issue. Here’s more from Cardiogram:
There is work to do before we start notifying our users of arrhythmias. First, we’d like to ensure that our algorithm works in a variety of conditions, whether you’re sleeping, running, or driving. Our detection algorithm has flagged some users who have opted into our study. We plan to send AliveCor devices to these users, and to a randomly selected control group. The ECG readings from these devices allow us to measure the accuracy of our algorithm on undiagnosed, ambulatory users.
There are challenges in scaling our model evaluation to run nearly continuously on all of our users. To deploy our algorithm in the wild, we must turn our research-grade machine learning setup in to a distributed model evaluation server.
Cardiogram is designed for the iPhone and can be downloaded now on the App Store for free. The watch app and complication show a graph of heart rate information in real time. On the iPhone side, users can view more details and historical trends.
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