Learning Preference-Based Objectives from Clinical Narratives for Dynamic Sepsis Treatment 事件

Learning Preference-Based Objectives from Clinical Narratives for Dynamic Sepsis Treatment arXiv:2604.10783v2 Announce Type: replace Abstract: Designing reward functions for reinforcement learning (RL) in healthcare remains challenging because clinically meaningful outcomes are sparse, delayed, and difficult to explicitly specify. Although structured clinical data capture physiologic states, they often fail to reflect broader aspects of patient trajectories such as treatment response, recovery