Fig. 3
From: CT-based whole lung radiomics nomogram for identification of PRISm from non-COPD subjects

Radiomics feature selection by using the least absolute shrinkage and selection operator (LASSO) logistic regression. (A) Selection of the tuning parameter (λ) in the LASSO model via 10-fold cross-validation based on minimum criteria. Binomial deviances from the LASSO regression cross-validation model are plotted as a function of log(λ). The y-axis shows binomial deviances and the lower x-axis the log(λ). Numbers along the upper x-axis indicate the average number of predictors. Red dots indicate average deviance values for each model with a given λ, and vertical bars through the red dots indicate the upper and lower values of the deviances. The vertical black lines define the optimal values of λ, where the model provides its best fit to the data. (B) The coefficients have been plotted vs. log(λ). (C) The 14 features with nonzero coefficients are shown in the plot