Stanford University Uses the Cloud to Detect Signs of Infection
Dr. Michael Snyder, Ph.D., professor and chair of genetics for Stanford University’s School of Medicine, delivered a keynote address as part of the AWS Public Sector Summit Online 2021 where he detailed how his team developed a smartwatch app to alert users when their bodies show signs of fighting an infection up to 10 days before they’re even aware of symptoms. The Stanford team had realized tracking pre-symptomatic COVID-19 cases through a less costly, more accessible method like wearables could help provide an early detection system. The app is powered by an algorithm that detects changes in an individual’s resting heart rate and step count. Early results are promising, and a pilot trial successfully alerted newly infected individuals as early as 10 days before they became aware of any symptoms. The app has entered the next phase of study, and the Stanford team is recruiting participants with the goal of reaching 10 million participants to increase its ability to detect signs of COVID-19 in real time. This smartwatch-based early detection system was built on AWS with the support of the AWS Professional Services team, who collaborated with the researchers to help the study scale its data processing pipeline.
“We have built up our data processing pipelines, and we’ll soon be building a data lake to combine this wearable data with our genomics data for researchers around the world to access, providing a collaborative platform to support the advancement of precision medicine as the first of its kind,” said Dr. Snyder.
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