Fig. 3. Generalization performance of the LiLNet model on the external validation set.

a–c display ROC curves for differentiating benign and malignant tumors in the HN external validation set. d provides ACC, F1, Reacll and Precision for this distinction. e presents ACC, F1, recall, and precision for identifying malignant tumors, while f shows the same metrics for Benign tumors. g The model’s ACC and AUC for HCC in the CD validation set. h The model’s ACC and AUC for HCC and ICC in the LS validation sets. i The ACC and AUC for distinguishing HCC and ICC in the GZ validation sets. Source data are provided as a Source Data file Source_data_Figure_3.xlsx.