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利用条件生成建模推动放射学人工智能的虚拟临床试验

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内容提要

本研究解决了放射学AI模型在真实临床应用中普遍存在的泛化能力不足的问题。我们提出了一种新颖的条件生成AI模型，用于虚拟临床试验，能够根据指定特征真实合成全身CT影像。该模型的关键发现为AI模型的稳定性评估提供了有效工具，有助于检测模型退化和算法偏见，推动放射学AI的安全应用。

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