Incentivizing Tool-Use Reinforcement Learning for Post-Arrival Emergency Care Prediction
arXiv:2610.21449v1 Announce Type: new Abstract: Large language models (LLMs) can reason over both structured measurements and free-text records, which makes them attractive for emergency department (ED) prediction. However, most existing LLMs still fall short of conventional ML methods like trees on EHR-based prediction tasks. Our controlled analysis traces this gap to two weaknesses: LLMs do not select informative features, and they misjudge what numerical values imply for risk even when given…