新闻
Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers developed nMAS, a multi-agent system that automates feature engineering from heart-failure electronic health records with evidence traceability and clinical guideline grounding.
- 为何重要
- Clinical data scientists and ML engineers building predictive models for heart-failure phenotyping need reproducible, auditable feature pipelines that integrate fragmented EHR data.
- 注意
- Evaluation used only 500 dummy records from a single institution. External validation on real patient data across multiple health systems is needed before production deployment.
收听本摘要
- agent
- llm
- language model
- reasoning
- rag
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