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Fig. 2 | Radiation Oncology

Fig. 2

From: A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma

Fig. 2

Selection of radiomics features before treatment via the least absolute shrinkage and selection operator (LASSO) Cox regression model. Tuning parameter (λ) selection in this model used tenfold cross-validation via the minimum criteria. A The Harrell’s concordance index (C-index) was plotted versus log(λ). Dotted vertical lines were drawn at the optimal values by using the minimum criteria and the 1 standard error of the minimum criteria (the 1-SE criteria), and the line on the right with λ value of 0.05284452 was chosen according to tenfold cross-validation. B LASSO coefficient profiles of the 278 radiomics features. A coefficient profile plot was generated versus value of log (λ). Two vertical lines were drawn at the value selected using tenfold cross-validation, where optimal λ pointed to 12 nonzero coefficients

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Radiation Oncology

ISSN: 1748-717X

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