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Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models

arXiv · AI, language, vision and robotics · article · Sep 10, 2026 · UTC

Electronic health record (EHR) foundation models trained on longitudinal patient trajectories have demonstrated strong performance across diverse clinical prediction tasks. However, their clinical reasoning capabilities remain constrained by next-token prediction on limited and incomplete EHR data. To address this, we propose a reinforcement learning (RL) fine-tuning framework that treats EHR foundation models as generative policies over patient trajectories. We formulate common clinical prediction problems (e.g., hospital readmission) as event-conditioned, time-windowed reasoning tasks. We th

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First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.