Radiological investigations have a high sensitivity for diagnosing COVID-19. We are a pro bono public health research initiative building the COVID-19 RADS and your contribution with scans and observations can help us build AI assisted reporting and data standards. We welcome Physicians, Public Health researchers and practitioners, Policy Makers, AI model builders and data science researchers, Pro bono initiatives, organizations and individuals dedicated to use the datasets and engineer scalable rapid screening solutions.
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The World Health Organization (WHO) declared the 2019–20 coronavirus outbreak a Public Health Emergency of International Concern (PHEIC) on 30 January 2020 and a pandemic on 11 March 2020.
COVID-19 RADS is a community intellect contribution driven Radiology Reporting and Data Standards for clinical management of COVID-19 symptomatic cases.
You can contribute scans or annotate cases in our library of X-Ray, CT and Ultrasound scans of suspicious COVID-19 cases, pneumonia and associated co-morbidities.Enroll and start contributing to build COVID-19 RADS.
You can contribute COVID-19 scans to our dataport and contribute to building the patient handling and clinical management protocol for Radiological scanning. Any other views are also welcome. Enroll and start contributing to build COVID-19 RADS.
You can contribute by analysing the data, relating Radiologists’ observations to diagnostic outcomes and algorithmically accelerate development of the COVID-19 RADS as well as build AI models to scale up Radiological rapid screen of symptomatic subjects.Enroll
You can contribute to the COVID-19 management strategy by making use of our whitepapers and listing of related literatures. You can also contribute a policy document which shall be of relevance to COVID-19 RADS. Enroll and start contributing to build COVID-19 RADS.
As a professional association of Engineers, Physicians, Scientists, Teachers and all, you have the ability to collectively create the knowledge base for COVID-19 RADS. Enroll and tell us how you wish to join us and contribute to the cause.
You can partner with us, exchanging anonymized data of relevance to building the COVID-19 RADS and list your initiative as a supporter to pool in our mutual strengths. Enroll and collaborate to co-build COVID-19 RADS.
Access the COVID-19 RADS sheets for reporting of X-Ray, CT and Ultrasound scans. Read more about how we are building the COVID-19 RADS with AI assistance, published case report and clinical literature, and your crowdsourced knowledge contribution.
As an AI model builder and data science researcher, you can gain access to X-Ray, CT and Ultrasound scans, annotations of observations in COVID-19 RADS, shared anonymously under for building image based screening models and to refine the COVID-19 RADS.
As a Radiologist you can contribute scans of suspicious cases and PCR if available to build a crowdsourced repository of case reports. Share anonymously under and these will be used for rapidly building AI driven radiology reporting and data standards.
See example scans annotated using the COVID-19 RADS to learn about observations in suspicious patients which indicate their differential diagnosis. All images and consolidated annotations are shared anonymously under
As a Radiologist you can contribute by annotating our existing library of cases with your observations. These crowdsourced annotations will be used for associating observations to diagnostic outcomes indicative of COVID-19, assisted by AI models to accelerate this process. Share anonymously under
Share your AI models for COVID-19 RADS improvisation and image classification on our model zoo, which can be accessed by others in the community for accelerating and scaling up radiological screening for COVID-19. Share your code base under Apache-2.0 and trained models under .
Launch of the portal and enrolment started.
COVID-19 RADS and whitepaper released.
Dataset access for AI Model builders
Data port open for contributions
Case reports available for browsing
AI Model Zoo launched
Debdoot Sheet, PhD
Tandra Sarkar, Radiologist
Nishant Chakravorty, PhD
Arunava Chakravarty, PhD
Manjira Sinha, PhD
Ronnie Rajan, MBBS
Velmurugan Balasubramanian, MBBS