English(EN) EHR2Trace: Auditable EHR Data Infrastructure for Patient World Models and Clinical Agents

新EHR2Trace系统为AI临床代理标准化患者数据

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员开发了EHR2Trace，一个旨在标准化和审计电子健康记录（EHR）数据以训练AI模型的系统。该基础设施解决了不同来源记录患者事件方式的不一致性问题，确保了可追溯性和可重复性。EHR2Trace将数百万个事件转换为共享表示，区分了医嘱、配药和给药，并已证明其能够检测注入的故障并揭示在未经整理的数据上训练的模型的性能膨胀。 AI

影响标准化电子健康记录数据，从而能够更可靠地训练和评估医疗保健应用的AI模型。

排序理由该集群包含一篇详细介绍新数据基础设施系统的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Xinye Yang, Yuli Wang, Cheng Ting Lin, Harrison Bai · 2026-10-01 04:00

EHR2Trace：面向患者世界模型和临床代理的可审计电子健康记录数据基础设施

arXiv:2609.38193v1 Announce Type: cross Abstract: Patient world models and clinical agents aim to predict changes in patients' health and support clinical work. Developing these systems requires reliable histories of patient conditions, treatments, and the information available a…

本文如何被排名

报道来源 [1]

EHR2Trace：面向患者世界模型和临床代理的可审计电子健康记录数据基础设施

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