Herndon, VA — Amazon Web Services (AWS) has unveiled new machine-learning tools reflecting—and beginning to tackle—some of the greatest challenges facing modern medicine. The suite of new capabilities empowers healthcare organizations to sift through enormous quantities of data of all different types. With novel computing power, AWS is providing new predictions and insights to researchers, whose teams would otherwise be powerless to take on datasets numbering in the millions.  

One new AWS product is called Sagemaker Ground Truth, which classifies and labels data in real time. The mammoth task of data labelling is too time-intensive and tedious for most organizations to carry out via sheer manpower. Also, these datasets are so big that approaching them with manpower alone tends to yield inaccuracies.

Amazon Elastic Inference, another brand-new tool, applies machine-learning power to the output from medical-imaging devices. Perhaps even more promising than the power of this tool is its commercial versatility. Amazon Elastic Inference employs a Graphics Processing Unit (GPU) unique in its scalability: customers can pay for just the amount of computing power they require and, later, adjust as required.

Finally, AWS’ Comprehend Medical bears revolutionary implications for clinical trials. Comprehend Medical is a cutting-edge machine-learning tool that can process unstructured data, referring primarily to doctors’ written and audio notes, which often contain more information than what’s placed on a bill or in an electronic health record. This “narrative” data is what must be sifted through in order to match clinical trials with eligible participants, and researchers often find that processing an individual’s unstructured data can take hours. Comprehend Medical can do it in seconds. 

This service is also HIPAA-eligible, identifying diagnoses, test results, and complete histories while keeping protected information secure. An application program interface (API) is available to facilitate integration into a company’s existing technological framework.

Why This Matters

Since Amazon’s acquisition of PillPack earlier this year, there’s been abundant speculation about Amazon’s healthcare vision. The release of these new AWS services shows that Amazon’s plans extend far beyond taking a bite out of retail drug sales. Rather, it may revolutionize healthcare at large. 

“The process of developing clinical trials and connecting them with the right patients requires research teams to sift through and label mountains of unstructured medical record data,” says Matthew Trunnell of the Fred Hutchinson Cancer Research Center, one of the earliest users of AWS’ new services. Comprehend Medical represents “a vital step toward getting researchers rapids access to the information they need when they need it so they can find actionable insights to advance life-saving therapies for patients.”

Syneos Health’s 2019 Health Trend Ten, available for download, explores the ten biggest trends re-shaping healthcare right now. Trend Four, “Search for the Right Patient,” features a section devoted to “New Seekers of Evidence.” These are the mammoth, pioneering healthcare partnerships—perhaps most notably, that of Amazon, Berkshire Hathaway, and JP Morgan—that promise to leverage their own, whole new realms of data, with the ultimate goal of stabilizing healthcare costs. Amazon’s new scalable machine-learning tools give us a taste of how they’ve already started making that a reality.

About the Author:

Ben helps spark innovative healthcare thinking as Associate Director of Innovation. Previously on the editorial staff of Vanity Fair, he brings experience in engaging, rigorous storytelling to the healthcare world. Ben’s goals are to move brands to rethink their roles, own their evolving narratives, and maintain vital and vigorous consumer relationships.