Swarm Learning

Our Vision and our Mission


ODELIA’s mission is to develop and implement a pan-European swarm learning network that enables privacy-preserving and democratic training of medical AI algorithms. By focusing on breast cancer detection in MRI screenings, the project aims to demonstrate the power of swarm learning and its potential applications in various clinical settings.

Our Vision for the Future

ODELIA envisions a future where swarm learning becomes a standard practice in the development of medical AI models, ensuring data privacy and fostering collaboration among healthcare institutions. The project aspires to pave the way for a new era of AI-driven medical advancements that empower healthcare providers and improve patient outcomes across Europe and beyond.


Fostering a strong, pan-European network of partners to collectively advance medical AI.


Developing groundbreaking swarm learning techniques to transform medical imaging and diagnostics.


Striving to improve patient outcomes and healthcare decision-making by applying AI-driven solutions to real-world clinical needs.

Privacy and Security

Ensuring patient data remains secure and confidential through decentralized training methods.


Creating open-source resources and tools, empowering the global research community and promoting widespread adoption.

Open Source - Open Access

Driven by practical, real-world goals and values

Project Context

In a rapidly evolving healthcare landscape, the need for advanced AI-driven solutions and secure data sharing has become increasingly important. ODELIA tackles these challenges by harnessing the power of swarm learning, providing a decentralized, privacy-preserving approach to AI model training. By addressing the limitations of traditional AI training methods, ODELIA paves the way for improved diagnostic accuracy and enhanced collaboration among healthcare providers. The project focuses on the critical area of breast cancer detection in MRI screenings, demonstrating the real-world impact of swarm learning on patient outcomes and advancing the field of medical AI.

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