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cs.LG2025
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…
cs.LG2024
Empirical Privacy Evaluations of Generative and Predictive Machine Learning Models -- A review and challenges for practice
Flavio Hafner, Chang Sun
Synthetic data generators, when trained using privacy-preserving techniques like differential privacy, promise to produce synthetic data with formal privacy guarantees, facilitatin…
cs.LG2024★ 116 cited
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…