AI algorithms

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Radiology Initiatives Illustrate Uses for Open Data and Open AI research

Fans of data in health care often speculate about what clinicians and researchers could achieve by reducing friction in data sharing. What if we had easy access to group repositories, expert annotations and labels, robust and consistent metadata, and standards without inconsistencies? Since 2017, the Radiological Society of North America (RSNA) has been displaying a model for such data sharing. That year marked RSNA's first AI challenge. RSNA has worked since then to make the AI challenge an increasingly international collaboration. Organizers of each challenge curate and annotate medical imaging studies and ask the research community to come up with models to answer important questions.

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RSNA Building an Open Repository of COVID-19 Imaging Data

Press Release | Radiological Society of North America (RSNA) | March 30, 2020

The medical imaging community around the world is uniting to help address the COVID-19 pandemic. The Radiological Society of North America (RSNA) continues to build on its extensive body of COVID-19 research and education resources, announcing a new initiative to build a COVID-19 Imaging Data Repository. The open data repository will compile images and correlative data from institutions, practices and societies around the world to create a comprehensive source for COVID-19 research and education efforts. The image hosting, annotation and analysis framework will enable researchers to understand epidemiological trends and to generate new AI algorithms to assist with COVID-19 disease detection, differentiation from other pneumonias and quantification of lung involvement on CT for prognosis or therapy planning.

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RSNA Launches International COVID-19 Open Radiology Database

Press Release | Radiological Society of North America (RSNA), RSNA COVID-19 AI Task Force | June 25, 2020

The Radiological Society of North America (RSNA) and the RSNA COVID-19 AI Task Force today announced the launch of the RSNA International COVID-19 Open Radiology Database (RICORD). RICORD is envisioned as the largest open database of anonymized COVID-19 medical images in the world. More than 200 institutions around the world have expressed their interest in participating. The database will include supporting clinical information and expert annotations. It will be freely available to the global research and education communities.

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