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05). The multivariate model integrating clinicopathological parameters and radiographic findings based on regression analysis achieved areas under the ROC curve (AUCs) of 0.936 and 0.912 in the primary and validation cohorts, respectively. The model generated by the support vector machine algorithm achieved AUCs of 0.914 and 0.948, respectively. We developed and validated multivariate models integrating endoscopic biopsy, tumor markers, CT morphological characteristics based on LAP, and CT texture parameters to predict LN metastasis in G
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