FoGS

A Filtered Mixture-of-Generators for Fully Synthetic Survival Training

FoGS is a new synthetic data method for survival analysis that improves model performance on scarce clinical data by filtering outputs from multiple generative models using real-data-trained survival scorers, enabling viable real-data substitution in privacy-restricted settings.