DarwinAI and Red Hat have accelerated the deployment of COVID-Net – a suite of deep neural networks for COVID-19 detection and risk stratification via chest radiography – to hospitals.
The companies are also leveraging the expertise of a computation research group, the Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC) at Boston Children’s Hospital to better focus the software for real world clinical and research use.
Since the launch of COVID-Net by DarwinAI and the University of Waterloo’s Vision and Imaging Processing (VIP) Lab , the project has evolved with collaboration from researchers and clinicians around the world.
The initiative eventually led to a collaboration between DarwinAI and Red Hat, using underlying technology from Boston Children’s Hospital.
The aim is to make it easier for clinicians to use COVID-Net in hospitals by means of a web-based graphical user interface (GUI) that sits on top of Boston Children’s ChRIS framework using Red Hat OpenShift – an enterprise Kubernetes platform that supports deployments across complex hybrid and multicloud infrastructures.
Rudolph Pienaar, Boston Children’s Scientist Rudolph Pienaar, lead Technical Architect of ChRIS and Assistant Professor in Radiology at Harvard Medical School, said: “We believe this effort can result in screening many cases at tremendous scale and help focus healthcare where it is most needed as quickly as possible.”
