Extraction of features and filtering to create a radiomics model
Of the 4785 radiomics features in the three phases, 2560 had good repeatability (ICC > 0.75), and the dimensionality reduction section was based on these features. A total of 597 features were significantly different by univariate analysis. The six most valuable features were selected from 597 features based on the Gradient Boosting Decision Tree and multivariate logistic analyses (Fig. 
The correlation diagram of the six effective features screened outRad-score = 0.9392–1.6715 × CMP-log_sigma_4_0_mm_3D_firstorder_Maximum.+ 1.7051 × UP-lbp_3D_m2_glrlm_ShortRunLowGrayLeveIEmphasis.– 1.0577 × CMP-wavelet_HHH_ngtdm_Complexity.+ 1.6901 × UP-wavelet-HLH_firstorder_Minimum.+ 1.2094 × NP-wavelet_HHL_firstorder_Median.+ 0.9787 × CMP-wavelet_HHL_glszm_SmallAreaLowGrayLeveIEmphasis.Figure 