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arXiv · 2610.38289

PulmoWorld: An Asynchronous Multimodal Medical World Model for Longitudinal Pneumonia Dynamics

Cheng Tang·Xinyu Zhang·Jiawei Chen·Minghui Zhang·Shaocong Wei·Wei Li·Yuxing Chen·Kongcheng Zhang·Chun-Mei Feng·Nanqing Dong·Xinyuan Zhu·Ziyan Huang·Junjun He·Yirong Chen·Lingtong Huang·Min Cen·Ming Hu
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Abstract

Pneumonia changes across respiration, inflammation, and organ function, while the measurements that describe it arrive at different times and are often incomplete. We introduce PULMOWORLD, a world model for longitudinal pneumonia dynamics that connects asynchronous state estimation, recursive simulation, and evidence-constrained planning. History-aware filtering separates state propagation from observation-driven correction, so a measurement updates the shared belief only when it is observed. That belief supports recursive forecasts of clinical values and modality representations, and summaries of future prognosis. Cap-MBRL searches imagined continuations inside an authorized action set and replaces a frozen fallback only when a candidate meets the risk budget and a predicted-cost margin. On the pneumonia cohort MASS, recursive forecasts are competitive with task-trained sequence models, and simulated future states retain prognostic information. Trained separately on public MIMIC-IV-CXR chest radiographs and clinical trajectories, this model improves prognostic discrimination over latest-value fusion in development and is competitive on long-horizon error on the locked pneumonia panel. In five known-mechanism MASS-Syn environments, Cap-MBRL lowers selection regret relative to direct fallback execution.

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Cheng Tang, Xinyu Zhang, Jiawei Chen, Minghui Zhang, Shaocong Wei, Wei Li, Yuxing Chen, Kongcheng Zhang, Chun-Mei Feng, Nanqing Dong, Xinyuan Zhu, Ziyan Huang, Junjun He, Yirong Chen, Lingtong Huang, Min Cen, Ming Hu. 2026-10-28. PulmoWorld: An Asynchronous Multimodal Medical World Model for Longitudinal Pneumonia Dynamics. https://arxiv.org/abs/2610.38289

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