研究人员推出CURA，一个旨在提高临床语言模型在风险预测中可靠性的新框架。CURA将模型的预测不确定性估计与个体错误概率和更广泛的群体模糊性进行对齐。这是通过一个两阶段过程实现的，包括领域特定的微调和一个考虑局部邻近数据的双层不确定性目标。 AI
影响 提高临床风险预测模型的可靠性，减少过度自信的虚假保证，以获得更好的决策支持。
排序理由 这是一篇介绍临床语言模型新框架的研究论文。
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CURA框架改进临床语言模型风险预测和不确定性校准
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- 这是一篇介绍临床语言模型新框架的研究论文。
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报道来源 [1]
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CURA：基于语言模型的临床不确定性风险对齐风险预测
arXiv:2604.14651v2 Announce Type: replace Abstract: Clinical language models (LMs) are increasingly applied to support clinical risk prediction from free-text notes, yet their uncertainty estimates often remain poorly calibrated and clinically unreliable. In this work, we propose…