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Table 2 Performances of the prediction models in the test set for 5-year mortality and 5-year metachronous liver metastasis

From: Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan

Predictors Logistic regression classification
AUC (mean +/− standard deviation)
Random forest classification
AUC (mean, standard deviation)
Prediction model for 5-year metachronous liver metastasis
 Clinical* 0.709 +/− 0.038 0.692 +/− 0.038
 PC1 0.606 +/− 0.044 0.557 +/− 0.043
 PC1-PC2 0.600 +/− 0.042 0.536 +/− 0.042
 PC1-PC3 0.588 +/− 0.040 0.503 +/− 0.046
 PC1-PC4 0.580 +/− 0.040 0.520 +/− 0.042
Clinical + PC1 0.747 +/− 0.036 0.697 +/− 0.038
 Clinical + PC1-PC2 0.744 +/− 0.036 0.676 +/− 0.043
 Clinical + PC1-PC3 0.740 +/− 0.038 0.668 +/− 0.042
 Clinical + PC1-PC4 0.736 +/− 0.038 0.691 +/− 0.042
Prediction model for 5-year mortality
 Clinical* 0.704 +/− 0.028 0.679 +/− 0.030
 PC1 0.482 +/− 0.031 0.511 +/− 0.030
 Clinical + PC1 0.695 +/− 0.031 0.647 +/− 0.033
  1. *Clinical: Age, Sex, T stage, N stage