Fig. 3.

Discrimination ability and correlation analysis of radiomics and deep learning (DL) features in the external test set 1. T-distributed stochastic neighbour embedding (t-SNE) visualizations for the radiomics features (A), two-dimensional (2D) DL features (B), and three-dimensional (3D) DL features (C) in the external test set 1. Each dot represents a patient. Blue dots indicate patients with lymph node metastasis (LNM), and red dots indicate patients without LNM. Hierarchical clustering heatmap for key radiomics features (D), top 2D DL features (E), and top 3D DL features (F) in the external test set 1. The x-axis represents the IDs of radiomics and DL features, and the y-axis represents 120 patients. Patients belong to the same cluster (adjacent rows) share similar features in the Euclidean space. The status of LNM is displayed on the white-green bar located on the left side next to the y-axis. Supplementary Table S2 provides the descriptions of the key radiomics features. (G) The correlation heatmap of key radiomics features, top 2D and 3D DL features in external test set 1, where the color represents the magnitude of the spearmen correlation coefficient, and the asterisks indicate P < 0.05. Red indicates radiomics.