Radiomics signature for liver metastasis prediction
REGRESSION
3906 radiomics features from T1w, T2w, and CE-T1w were used to establish a prediction model. In the development and validation cohort, the LASSO-SVM model resulted in AUCs of 0.878 and 0.815, respectively; the LASSO-LR model got AUCs of 0.870 and 0.821, respectively; the RF-SVM model calculated the AUCs as 0.788 and 0.736, respectively; the RF-LR model resulted in AUCs of 0.840 and 0.710, respectively; the PCA-SVM model leaded to AUCs of 0.794 and 0.756, respectively; and the PCA-LR model induced the AUCs of 0.825 and 0.762, respectively (Additional file LASSO regression for radiomics features selection. 