- Healthcare Orgs Report Improved Processes, Patient Experience with AWS
- Amazon Launches Service for Big Data Analytics in Healthcare
Under the collaboration, faculty from UNC-Chapel Hill’s health research labs will utilize a cloud-native “software factory,” enabling them to develop solutions that run on AWS for validation and commercialization via UNC-based health startups.
“AWS is leading the way in making software development much easier than it has ever been. Many AWS solutions require little to no coding, which makes innovation more accessible to our talented faculty,” said Christopher Clemens, UNC-Chapel Hill provost, and chief academic officer, in the press release. “This new collaboration is the perfect marriage for University faculty and researchers who do not have a deep software developer background but have the ideas and research in place to advance healthcare.”
Selected projects will leverage Amazon SageMaker, Amazon Rekognition, other AWS data solutions, and artificial intelligence (AI) and machine learning (ML) managed services. They will also collaborate with AWS solutions architects to support product development.
“Many of our researchers are developing transformative AI/ML algorithms that can help advance precision medicine and digital therapeutics,” said Eshelman Institute for Innovation’s Bob Dieterle, managing director of UNC-Chapel Hill’s Digital Health Venture Studio, in the press release. “With this approach, researchers can drop algorithms into a reusable container, snap together a mobile app front end along with a secure backend database, and deploy directly to enrolled patients in their studies.”
Eight of the 25 projects are underway. One project is using AI to bolster product safety and quality assurance challenges caused by contamination issues with compounded medicines, which the press release notes can lead to serious illness or death.
To address this, researchers from the UNC Eshelman School of Pharmacy are using Amazon Rekognition to develop a computer vision solution for training, ongoing competency assessments, and regulatory documentation. The solution allows researchers to monitor movements during the sterile compounding process, compare the movements against established best practices, and generate reports that indicate breaches in technique.
In recent years, other healthcare stakeholders have also teamed up with AWS to support innovation and big data analytics.
In 2019, the Pittsburgh Health Data Alliance (PHDA) launched a partnership with AWS to use ML to improve medical imaging, cancer diagnostics, precision medicine, voice-enabled technologies, and other areas of healthcare through accelerated research and product commercialization.
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