2025-05-20 –, Showroom
Are you a researcher with an algorithm, who would like to challenge your peers to do better? Or do you have a dataset that needs annotating, but your colleagues work on the other side of the globe? You can do both, and more, on grand-challenge.org. Join this session to learn more about our cloud-based platform featuring challenges, reader studies and algorithms!
Are you looking for a way to develop AI models safely and transparently? After this session you will have learned about all the features of the open-source, cloud-based Grand Challenge platform, and how it enables you to accelerate your research in AI.
We’ll start with a brief overview of the key steps in AI development before diving into how the Grand Challenge platform, an open-source initiative, streamlines the process. Learn how the platform enables you to:
Compare your algorithm against other algorithms using our Challenges feature, where you can compete with other AI developers in a scalable environment.
Seamlessly handle user management, data security, and scalability, with robust infrastructure designed for handling large quantities of sensitive data.
Leverage the Reader Study feature to gain insights into your dataset—whether through questions or annotations. This helps train annotators, establish clinical benchmarks, and improve your models.
Run and test AI models effortlessly, using a cloud-based platform that eliminates the need for local hardware and simplifies deployment.
By harnessing the power of cloud computing, Grand Challenge provides a secure, scalable, and collaborative environment for AI development. As an open-source platform, it fosters transparency and innovation in research. Join us to see these features in action and discover how our platform can accelerate your research!
I'm Product Owner for the Grand Challenge platform, developed at the Radboud University Medical Center. Grand Challenge is a platform for the end-to-end development of AI in medical imaging., an open-source, cloud-based initiative.