Reproducibility analysis and feature selection
REGRESSION
Given concerns about the reproducibility of radiomic features, we performed an intra-observer reproducibility analysis. One author segmented 50 randomly chosen images at two-time points with an interval time of one month, producing two VOIs of each selected patient. Agreement between feature extractions was assessed using intra-class correlation coefficients (ICCs). An ICC value greater than 0.8 indicated good agreement. To eliminate redundant radiomic features, we performed a two-step feature selection strategy. MRMR was initially used to select the 20 most valuable features. The LASSO method, which is suitable for the regression of high-dimensional data (