arXiv AI September 10, 2026 By Suyang Xi, Songtao Hu, Shansong Wang, Mojtaba Safari, Luke del Balzo, Ehsan Ul Karim, Mingzhe Hu, Kuo Zhang, Tonghe Wang, Ralph R. Weichselbaum, Xiaofeng Yang

A radiographic world model for clinical reasoning and evidence generation

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The paper introduces MedDream, a radiographic world model that learns a shared continuous latent state from paired chest radiograph-text observations. MedDream outperforms existing diagnostic and generative AI models across eight clinical datasets, improving diagnostic reasoning, resident concordance, and evidence generation. Targeted synthetic augmentation guided by subgroup performance gaps further enhances model performance, particularly for Asian patients.

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