Federated Learning Technology

CAFEIN (Computational Algorithms for Federated Environments: Integration and Networking) is an innovative AI-based tool developed and hosted by CERN to support clinicians, patients, and caregivers in the analysis, diagnosis, and prognosis of diseases.

Built on a robust Federated Learning (FL) infrastructure, CAFEIN allows multiple institutions to collaboratively develop trustworthy AI models using diverse clinical and patient data, without compromising data privacy. Instead of sharing sensitive data, institutions train AI models locally and share only encrypted model parameters. This preserves confidentiality while enabling the creation of powerful, data-driven predictive tools.

The federated platform behind CAFEIN features:

• A modular interface to easily configure and deploy FL processes adapted to various medical applications.
• A network infrastructure designed to ensure data security, including advanced protection against threats such as data poisoning and model inversion.
• A secure parameter server, specifically built to withstand targeted security attacks.

Through this federated approach, CAFEIN empowers the development of medical AI applications, such as:

• Brain MRI anomaly screening
• Multi-pathology detection and classification

By combining cutting-edge AI techniques and strict data protection measures, CAFEIN aims to bring concrete benefits to healthcare research and practice, fostering collaboration without sacrificing patient privacy.