[Retracted] Value of CT Radiomics and Clinical Features in Predicting Bone Metastases in Patients with NSCLC

Figure 2

LASSO-logistic regression screening for the radiomic characteristics of NSCLC patients with bone metastasis. (a) Convergence graph of 51 radiomic feature coefficients, the horizontal axis is log lambda, and the vertical axis is the radiomic feature weighting coefficient; (b) cross-validation graph, the horizontal axis is log(lambda). The vertical axis is MSE. Different lambda values correspond to different MSEs. The vertical dotted line in the figure represents the number of optimal radiomic features selected by LASSO regression using 5-fold cross-validation. According to the minimum MSE criterion, when λ = 0.0160, the optimal model is obtained; (c) finally, 7 radiomic features were selected.

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