FRESH: Information-Geometric Calibration of Patient-Level Models to Aggregate Evidence
FRESH combines patient-level data models with population-level summary statistics like clinical trials into a unified, data-efficient framework for clinical decision making. It recalibrates a generative model to match aggregate outcomes, allowing researchers to contextualize single trial results against real-world evidence and estimate treatment effects.