NutriOrion：一种基于临床指南的个性化营养干预分层多智能体框架
NutriOrion: A Hierarchical Multi-Agent Framework for Personalized Nutrition Intervention Grounded in Clinical Guidelines
AI总结：
NutriOrion通过分层多智能体框架实现个性化营养干预，结合多目标优先级算法和安全约束机制，有效解决多病共存患者的饮食需求冲突与临床有效性问题。
摘要：
针对多病共存患者个性化营养干预对改善健康结果的重要性，但需要同时整合异质性临床状况、药物和饮食指南，这一过程具有挑战性。单智能体大语言模型（LLM）在处理高维患者资料时常出现上下文过载和注意力稀释问题。我们引入NutriOrion，一种具有并行后顺序推理拓扑结构的分层多智能体框架。NutriOrion将营养规划分解为具有隔离上下文的专业领域智能体，以减轻锚定偏差，随后进行条件细化阶段。该框架包含一个多目标优先级算法，用于解决冲突的饮食需求，并包含一个安全约束机制，在合成过程中注入药理学禁忌作为硬负约束，通过构建而非事后过滤确保临床有效性。为实现临床互操作性，NutriOrion将合成的见解映射到ADIME标准和FHIR R4资源。在330名多病共存中风患者上评估，NutriOrion优于多个基线，包括GPT-4.1和替代多智能体架构。它实现了12.1%的药物-食物相互作用违规率，显示出与推荐风险营养素之间负相关（-0.26至-0.35）的强个性化，以及临床有意义的饮食改善，包括纤维增加167%、钾增加27%，同时钠（9%）和糖（12%）减少。
英文摘要：
Personalized nutrition intervention for patients with multimorbidity is critical for improving health outcomes, yet remains challenging because it requires the simultaneous integration of heterogeneous clinical conditions, medications, and dietary guidelines. Single-agent large language models (LLMs) often suffer from context overload and attention dilution when processing such high-dimensional patient profiles. We introduce NutriOrion, a hierarchical multi-agent framework with a parallel-then-sequential reasoning topology. NutriOrion decomposes nutrition planning into specialized domain agents with isolated contexts to mitigate anchoring bias, followed by a conditional refinement stage. The framework includes a multi-objective prioritization algorithm to resolve conflicting dietary requirements and a safety constraint mechanism that injects pharmacological contraindications as hard negative constraints during synthesis, ensuring clinical validity by construction rather than post-hoc filtering. For clinical interoperability, NutriOrion maps synthesized insights into the ADIME standard and FHIR R4 resources. Evaluated on 330 stroke patients with multimorbidity, NutriOrion outperforms multiple baselines, including GPT-4.1 and alternative multi-agent architectures. It achieves a 12.1 percent drug-food interaction violation rate, demonstrates strong personalization with negative correlations (-0.26 to -0.35) between patient biomarkers and recommended risk nutrients, and yields clinically meaningful dietary improvements, including a 167 percent increase in fiber and a 27 percent increase in potassium, alongside reductions in sodium (9 percent) and sugars (12 percent).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
