T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

Figure 4 The selection process of the least absolute shrinkage and selection operator method. A: 10-fold cross-validation and minimization of standard selection parameters (lamdba) in the least absolute shrinkage and selection operator model; B: Eight radiomic features with nonzero coefficients were selected for the optimal parameter lamdba (lambda = 0.0146). MSE: Mean square error.