CAREAgent: Clinical Agent with Structured Reasoning and Tool-Integrated for Order Generation
Clinical order generation serves as a critical bridge between clinical decision-making and real-world practice, translating medical decisions into concrete and executable orders. Existing agents mainly focus on coarse-grained decisions and overlook the fine-grained, executable information required for clinical orders. To address this gap, we propose CAREAgent, an agent for clinical order generation. To support its training, we introduce a two-stage agentic reasoning data construction method. First, we design an agent framework that constructs verifiable reasoning trajectories aligned with realistic clinical tool usage. Second, we filter reasoning trajectories by format compliance, order v...
| Authors | Ruihui Hou, Ziyue Huai, Chennuo Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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