English(EN) Patient-Centered Treatment Planning for Chronic Multimorbidity: A Hierarchical Reinforcement Learning Framework for Preference Modeling

新的HRL框架将患者偏好纳入慢性病治疗规划

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 04:00

研究人员开发了一个新的层级强化学习框架，名为以患者为中心的因子动作层级选项-批评器（FAHOC）。该框架旨在通过将患者偏好直接纳入决策过程，来改进多慢性病患者的治疗规划。使用约50,000名患者的数据进行的评估表明，FAHOC可以显著提高质量调整生命年，并准确识别患者偏好。 AI

影响该框架通过更好地将临床建议与患者偏好相结合，有望为多慢性病患者带来更个性化、更有效的治疗方案。

排序理由该条目是一篇学术论文，详细介绍了一种用于特定AI应用的新框架。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Nafiseh Payani, Soham Das, G. Anthony Wilson, Anahita Khojandi · 2026-10-02 04:00

面向慢性多重疾病的以患者为中心的治疗规划：用于偏好建模的层级强化学习框架

arXiv:2609.39911v1 Announce Type: new Abstract: Patient preference, defined as a patient's demonstrated willingness and capacity to adhere to clinical recommendations, is a primary determinant of therapeutic effect yet remains structurally absent from existing computational treat…