116 citations · 116 across the 5 of their papers we have counts for
5 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 enables fair and zero shot medical image generation across demographic intersections through compositional diffusion
Mahmoud K. Ibrahim, Mahmoud Ibrahim, Bart Elen +7
Medical image generators trained on imbalanced data can fail at demographic intersections absent from training. We introduce CompDiff, which encodes age, sex and race separately an…
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…
Adapting Lightweight Vision Language Models for Radiological Visual Question Answering
Aditya Shourya, Michel Dumontier, Chang Sun
Recent advancements in vision-language systems have improved the accuracy of Radiological Visual Question Answering (VQA) Models. However, some challenges remain across each stage…
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…