构建可管控的医疗AI能力生态，实现长期临床服务的可信协同。
Clinical Harness for Governable Medical AI Skill Ecosystems
- 提出临床AI技能概念与运行时治理架构
- 在骨质疏松症中验证多源技能协同支持全周期诊疗
- 适合医疗AI系统设计者与临床决策支持研究者
当前医疗AI仍以孤立模型为主，而临床需求要求具备可追溯、持续可用的能力。本文定义临床AI技能，并提出临床挂钩（Clinical Harness）运行时治理架构，实现技能的注册、编排、约束与监控。以骨质疏松症为例，展示知识驱动、数据驱动及物理增强型技能如何协同支持全生命周期护理，并为未来医疗智能体提供可管控的基础支撑。
原文摘要 · Abstract (English)
Medical AI remains organized around isolated models, whereas care requires accountable capabilities that persist across time. We define clinical AI skills and propose the Clinical Harness, a runtime governance architecture that registers, orchestrates, constrains and monitors them. Using osteoporosis as an exemplar, we show how knowledge-driven, data-driven and physics-enhanced skills can support lifecycle care and provide a governed substrate for future medical agents.
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