How Federated Learning is Solving the Rare Disease Diagnostic Gap

Rare diseases affect over 300 million people globally, yet knowledge remains fragmented due to data silos.

Federated Learning allows AI to train on distributed data without requiring patient information to leave the hospital.

Models using federated architecture have achieved up to 99% of the efficiency of centralized data training.

Tools like DxGPT are already helping over 6,000 physicians in Madrid navigate complex diagnostic challenges.