Article

Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data

2025-11-24

Abstract excerpt

<title>Abstract</title> <p>Achieving robust performance and fairness across diverse patient populations remains a central challenge in developing clinically deployable deep learning models for diagnostic imaging. Synthetic data generation has emerged as a promising strategy to address current limitations in dataset scale and diversity. In this study, we introduce RoentGen-v2 , a state-of-the-art text-to-image dif...

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Literature Corpus work: e98b5423-e8fe-5922-8e7d-a349872003d1
DOI: 10.21203/rs.3.rs-7687810/v1

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