4 papers
Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers
Mahmoud Ibrahim, Bart Elen, Chang Sun +2
Per-subgroup fairness audits of medical image classifiers face a sample-size problem: minority subgroups in held-out test sets have so few samples that the resulting confidence int…
CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation
Mahmoud Ibrahim, Bart Elen, Chang Sun +2
Generative models are increasingly used to augment medical imaging datasets for fairer AI, yet a key assumption often goes unexamined: that generators produce equally high-quality…
Enabling Granular Subgroup Level Model Evaluations by Generating Synthetic Medical Time Series
Mahmoud Ibrahim, Bart Elen, Chang Sun +2
We present a novel framework for leveraging synthetic ICU time-series data not only to train but also to rigorously and trustworthily evaluate predictive models, both at the popula…
Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges
Mahmoud Ibrahim, Yasmina Al Khalil, Sina Amirrajab +6
This paper presents a comprehensive systematic review of generative models (GANs, VAEs, DMs, and LLMs) used to synthesize various medical data types, including imaging (dermoscopic…