HERMES：基于临床笔记的对比感知知识图谱推理用于患者结局预测
HERMES: Contrast-Aware Knowledge Graph Reasoning from Clinical Notes for Patient Outcome Prediction
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中文总结 AI 辅助
HERMES提出基于临床笔记构建个性化知识图谱并结合对比逻辑建模与图注意力网络，在MIMIC-III和MIMIC-IV上显著提升患者结局预测性能。
中文摘要 AI 辅助
临床预测模型通常依赖于结构化电子健康记录数据，如时间序列和程序代码。尽管近期方法已开始利用非结构化临床笔记，但它们通常将这些笔记编码为扁平序列，这可能丢失临床叙述中存在的显式关系和时序结构。为此，我们提出HERMES，一个仅基于临床文本运作并保留临床关系的图框架。该方法基于两个关键思想。首先，通过大语言模型引导的从临床笔记中提取，结合对比逻辑建模，构建个性化知识图谱，该建模显式捕捉时间动态、治疗失败和结局变化。其次，图注意力网络通过基于图的学习综合患者表示。在MIMIC-III和MIMIC-IV上针对院内死亡率和30天再入院预测的实验表明，HERMES持续优于强文本基线。我们的发现证明，结合对比逻辑建模的显式关系建模显著提升了预测性能。
英文摘要
Clinical predictive models often rely on structured Electronic Health Record data, such as time-series and procedure codes. While recent approaches have begun leveraging unstructured clinical notes, they typically encode them as flat sequences, which may lose explicit relational and temporal structure present in clinical narratives. In response, we propose HERMES, a graph-based framework that operates exclusively on clinical text while preserving clinical relationships. This approach builds on two key ideas. First, personalized Knowledge Graphs (KGs) are constructed through Large-Language-Model-guided extraction from clinical notes with Contrastive Logic Modeling that explicitly captures temporal dynamics and treatment failures and changes in outcomes. Second, a Graph Attention Network synthesizes patient representations through graph-based learning over the KGs. Experiments on MIMIC-III and MIMIC-IV for in-hospital mortality and 30-day readmission prediction show that HERMES consistently outperforms strong text-only baselines. Our findings demonstrate that explicit relational modeling with Contrastive Logic Modeling significantly advances predictive performance.
发表机构
- Business AI Lab, College of Technology, National Economics University（国民经济大学技术学院商业人工智能实验室）
- Hanoi University of Science and Technology（河内理工大学）
- A2I Lab, Phenikaa School of Computing, Phenikaa University（Phenikaa大学Phenikaa计算学院A2I实验室）
- Department of Head and Neck Surgery, Vietnam National Cancer Hospital & Hanoi Medical University（越南国家癌症医院头颈外科与河内医科大学）
- VNPT AI, VNPT Group（VNPT集团VNPT AI）
机构由 AI 辅助整理，请以论文原文为准。
