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Can you predict who will develop severe COVID-19 from a chest CT scan?

16 Dec. 2021 by Bram van Ginneken, Alexander Lemm, Luuk Boulogne and Anne Mickan

Last week, we opened STOIC2021: A COVID-19 AI challenge with 10,000 CT scans. Together with its participants, we aim to find the best solution for predicting who will develop severe COVID-19 from a chest CT scan. We will make the final solution easily accessible for everyone. In total, $20,000 in AWS Credits will be awarded to the winning teams.

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AI challenges, data, and algorithms

4 March 2021 by Bram van Ginneken

Presentation by Bram van Ginneken held during the European Congress of Radiology 2021 on the how and why of challenges in medical image analysis.

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Why Challenges?

14 Feb. 2021 by Keelin Murphy and Bram van Ginneken

This is an updated version of blog post made years ago when we launched our platform It makes the case for challenges and provides some advice for those interested in setting up their own challenge.

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Create Your Own Challenge

21 Jan. 2021 by Kiran Vaidhya Venkadesh, Khrystyna Faryna, James Meakin, Bram van Ginneken and Ecem sogancioglu

This blog post provides instructions for creating your own challenge on along with videos of an example challenge.

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Visualisations For Challenges

6 Nov. 2020 by James Meakin, Adriƫnne Mendrik, Maarten van Meersbergen, J.G. Gonzalez and Berend Weel

Visualizations of algorithm results beyond the challenge leaderboard can aid in gaining insight into algorithm performance for a specific task and in finding new research directions. offers an option to add visualizations to your challenge through ObservableHQ notebooks. You can use Vega or Vega-lite to easily create graphs and the Vega Editor to edit them, before integrating them in your ObservableHQ notebook that will be embedded in your challenge page on To get you started, we provided a couple of example notebooks for different types of challenges (e.g. a classification, segmentation and detection challenge).

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