In the news
LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- LongAgent, an agent-based system, autonomously searches medical variable combinations and temporal windows to predict patient outcomes from longitudinal data.
- Why it matters
- Healthcare engineers building predictive models from multi-source, irregularly-sampled patient records need automated feature and aggregation selection.
- Watch out
- Real clinical dataset results match baselines rather than exceed them; synthetic data improvements are modest and statistical significance is marginal.
- agent
- agentic
The patterns behind this
- Process Reward Models & Verifier-Guided Search
- Multi-Source Context Fusion
- Temporal Knowledge Graph Memory
Each one covers how the technique works, when it earns its cost, and where it breaks.
The Agent Architect
One pattern, one tradeoff, one production failure story. A short weekly briefing for people building agentic systems.
Weekly email, one-click unsubscribe. We only use your address to send the briefing.