新闻
LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction
arXiv cs.AI · 发布于 · 阅读约3分钟
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- 发生了什么
- LongAgent, an agent-based system, autonomously searches medical variable combinations and temporal windows to predict patient outcomes from longitudinal data.
- 为何重要
- Healthcare engineers building predictive models from multi-source, irregularly-sampled patient records need automated feature and aggregation selection.
- 注意
- Real clinical dataset results match baselines rather than exceed them; synthetic data improvements are modest and statistical significance is marginal.
- agent
- agentic
这条新闻背后的模式
- Process Reward Models & Verifier-Guided Search
- Multi-Source Context Fusion
- Temporal Knowledge Graph Memory
每个模式都讲清楚技术如何运作、何时值得投入，以及在哪里会失效。
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