3 papers
cs.LG2025
Training Together, Diagnosing Better: Federated Learning for Collagen VI-Related Dystrophies
Astrid Brull, Sara Aguti, Véronique Bolduc +9
The application of Machine Learning (ML) to the diagnosis of rare diseases, such as collagen VI-related dystrophies (COL6-RD), is fundamentally limited by the scarcity and fragment…
cs.LG2025
Federated Learning for Pediatric Pneumonia Detection: Enabling Collaborative Diagnosis Without Sharing Patient Data
Daniel M. Jimenez-Gutierrez, Enrique Zuazua, Joaquin Del Rio +2
Early and accurate pneumonia detection from chest X-rays (CXRs) is clinically critical to expedite treatment and isolation, reduce complications, and curb unnecessary antibiotic us…
cs.LG2025
The Sherpa.ai Blind Vertical Federated Learning Paradigm to Minimize the Number of Communications
Alex Acero, Daniel M. Jimenez-Gutierrez, Dario Pighin +3
Federated Learning (FL) enables collaborative decentralized training across multiple parties (nodes) while keeping raw data private. There are two main paradigms in FL: Horizontal…