Radiomics is a promising tool for the identification of new prognostic biomarkers. Radiomic features can be affected by different scanning protocols, often present in retrospective and prospective clinical data. We compared a computed tomography (CT) radiomics model based on a large but highly heterogeneous multicentric image dataset with robust feature pre‐selection to a model based on a smaller but standardized image dataset without pre‐selection.

中文翻译：

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比较稳健和标准化的 CT 影像组学模型，以预测非小细胞肺癌患者的总生存期。

放射组学是识别新预后生物标志物的有前途的工具。放射学特征可能会受到不同扫描协议的影响，这些协议通常存在于回顾性和前瞻性临床数据中。我们将基于具有鲁棒特征预选功能的大型但高度异构的多中心图像数据集的计算机断层扫描 (CT) 放射组学模型与基于较小但没有预选的标准化图像数据集的模型进行了比较。