Life Sciences and eHealth
PuReGoMe
Understanding Dutch public sentiment during the COVID-19 outbreak period by analyzing real-time...
Diagnostic imaging with computed tomography (CT) and chest X-ray are proving increasingly important in detecting and assessing disease severity of COVID-19. To aid in the clear communication between radiologists and clinicians the Radiological Society of the Netherlands (NVvR) has proposed a standardised reporting system, CO-RADS, for assessing the suspicion and severity of COVID-19 in a CT scan. In this project, an existing platform, grand-challenge.org (with elements of the the EYRA benchmark platform, where suitable), will be furthered to enable the development and deployment of machine learning algorithms for automated scoring of CT scans using the CO-RADS system.
Research team: James Meakin, Paul Gerke, Mike Overkamp and Miriam Groeneveld, Prof. Bram van Ginneken (Radboud UMC)
eScience Research Engineers: Maarten van Meersbergen, Pushpanjali Pawar, Jesus Garcia González
Partners
Related
Related projects
Life Sciences and eHealth
FAIR Data for CAPACITY
Statistical analyses and machine learning models: Insights about the relation between...
Life Sciences and eHealth
Retina COVID19
Social distancing measures carry economic and social costs
eScience Methodology
Enhance Your Research Alliance (EYRA) Benchmark Platform
Supporting researchers to easily set-up benchmarks
Let’s collaborate
Are you a researcher who could benefit from our eScience skills and experience? Reach out to us today and let’s explore how we can work together.
Collaborate
Updates