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EJNMMI Physics
Fig. 2 | EJNMMI Physics

Fig. 2

From: Development and validation of a prognostic nomogram model in locally advanced NSCLC based on metabolic features of PET/CT and hematological inflammatory indicators

Fig. 2

Feature selection using the least absolute shrinkage and selection operator (LASSO) Cox regression model. LASSO coefficient profiles of the 10 features. Selection of tuning parameter (λ) in the LASSO regression using 10-fold cross-validation via minimum criteria. At the optimal values log (λ), where features are selected, two dotted vertical lines were drawn at the optimal scores by minimum criteria and 1-s.e. criteria (A), Coefficient profile plot was produced against the log(λ) sequence. (B)

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