MedRSI: Recursive Self-Improvement for Medical Agents via Clinically Aligned Self-Evolution· 医疗代理的递归自我改进
Medical agents increasingly combine general reasoning models with specialized clinical tools, yet their capabilities remain largely fixed by what clinicians and engineers design before deployment. Recursive self-improvement (RSI) offers a different paradigm in which agents learn from their own failures and autonomously expand their capabilities, but directly applying RSI to medicine introduces fundamental safety challenges. We introduce MedRSI, the first recursive self-improvement framework for medicine, which continuously transforms diagnostic failures into new clinical capabilities through tool composition and task-specific model training. Inspired by clinical practice, MedRSI introduces two mechanisms for clinically aligned self-evolution. Clinical-cost-aware failure prioritization dire
医疗代理通过递归自我改进实现临床失败向新能力的转化。
- 核心方法
- MedRSI框架通过工具组合和任务特定模型训练，将诊断失败转化为新的临床能力；引入临床成本意识的失败优先级和自我演化机制。
- 适合谁读
- 研究者、工程师、医疗领域AI应用开发者
- 要解决的问题
- 现有医疗代理的能力在部署后基本固定，缺乏自主学习和改进的能力。
- 关键实验
- 未提供
- 主要贡献
- 提出首个医疗领域递归自我改进框架MedRSI，提升医疗代理自主学习与自我扩展能力。
- 意义与局限
- 此框架有望提升医疗代理的诊断准确性和适应性，但需解决安全性问题；对医疗AI的长远发展具有重要影响。