ATRIA让心电图报告可追溯、可修改，像医生一样逐步完善诊断。
ATRIA: Adaptive Traceable ECG Reporting with Iterative Agents
- 多智能体分步生成报告，每条结论都绑定证据
- 支持中途添加新信息并回溯修改，避免错误累积
- 已适配临床现有分析模型，适合医疗团队协作使用
现有心电图报告生成方法将解读与报告耦合在一起，错误难以追溯和修正；而基于智能体的系统虽任务解耦，但仅单次执行，无法回溯。临床心电图报告实际是迭代过程，需逐步整合上下文并双向修改。我们提出 extsc{ATRIA}，一种模拟临床医生迭代工作流的多智能体心电图报告系统：它为每项报告结论绑定支持证据，标记无证据支撑的陈述，支持会话中引入新上下文，并允许医生验证或修改个别发现，而非接受单一不可解释输出。其智能体使用已在临床使用的心电图分析模型，确保结果可信；作为云端网页服务，可立即部署。通过四个交互案例演示，附有实时演示和视频。
原文摘要 · Abstract (English)
Existing ECG report generation is tightly coupled -- interpretation and reporting fused end-to-end, so errors propagate without stage-level recourse -- while agent-based systems decouple tasks but remain single-pass, never revisiting earlier outputs. Clinical ECG reporting instead unfolds iteratively, requiring progressive context integration and bidirectional editing. We present \textsc{ATRIA}, a multi-agent ECG reporting system that mirrors the clinician's iterative workflow: it binds every report claim to its supporting evidence, flags statements unsupported by that evidence, incorporates additional context mid-session, and lets clinicians verify and revise individual findings rather than accept one opaque output. Because its agents use ECG analysis models already in clinical use, the underlying findings are clinically trustworthy; and as a cloud-based web service, \textsc{ATRIA} is ready for immediate deployment. We demonstrate \textsc{ATRIA} through four interaction cases, with a live demo and video available.
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