2 papers
cs.LG2025
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Bradley Segal, Joshua Fieggen, David Clifton +1
Ensuring the generalisability of clinical machine learning (ML) models across diverse healthcare settings remains a significant challenge due to variability in patient demographics…
eess.IV2020
Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs
Bradley Segal, David M. Rubin, Grace Rubin +1
Chest x-rays are a vital tool in the workup of many patients. Similar to most medical imaging modalities, they are profoundly multi-modal and are capable of visualising a variety o…