A federated approach that trains a global generator on synthetic patient timelines produced by local models, preserving most but not all zero-shot prediction performance.
Survey of medical applications of federated learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Federated Timeline Synthesis: Scalable and Private Methodology For Model Training and Deployment
A federated approach that trains a global generator on synthetic patient timelines produced by local models, preserving most but not all zero-shot prediction performance.