NETHERLANDS

Challenges Framework Flagship Node

The Grand Challenge (GC) platform is a digital research infrastructure providing a suite of services to support the development and benchmarking of AI algorithms in medical imaging and related fields.

The platform provides three core interoperable services: challenges, reader studies, and controlled algorithm execution.

Challenges are competitions designed to identify the best-performing AI algorithm for a specific task, evaluated against a defined set of metrics. Organizers provide a training dataset, a test dataset, a task description, and the evaluation metrics. Participants download the training data, develop their algorithm, and submit it as a solution.

Reader studies enable the collection of structured annotations or clinical assessments on a defined dataset. By presenting a set of questions to clinicians or annotators, organizers produce enriched datasets that can serve as training data, test data, or a clinical benchmark within a challenge.

Algorithms developed by platform users or challenge participants can be shared with others through public or restricted access. In both cases, strict access controls are enforced, ensuring data privacy and intellectual property protection for all parties.

Read more about the three services here.

The three services on the GC platform are designed to work together, enabling end-to-end AI development and validation workflows. Algorithm outputs can be directly fed into a reader study, allowing clinicians or annotators to review, assess, or enrich the results produced by an algorithm. Reader studies, in turn, can be integrated into challenges — either as a source of training or test data, or as a mechanism for clinical benchmarking of submitted solutions. Finally, algorithms that emerge from a challenge can be published on the platform, making them available to the broader user community. This interconnected design allows organizers, developers, and clinicians to move seamlessly from data collection and annotation, through algorithm development and benchmarking, to deployment and shared access. 

The services are aligned with FAIR data principles and support secure, privacy-preserving analysis workflows, enabling data to be accessed, processed, and evaluated. In this way, Grand-Challenge contributes to emerging European data space initiatives, such as the European Health Data Space (EHDS), by facilitating secondary use of health data for research and innovation under controlled conditions

Offered Technologies:

Technologies
Challenges Framework

• Challenges
• Reader studies
• Algorithms

Contact details

Miriam Groeneveld – Product owner Grand-Challenge Radboudumc

Radboudmc
miriam.groeneveld@radboudumc.nl
www.grand-challenge.org