Skip to main content
Fig. 2 | BMC Pulmonary Medicine

Fig. 2

From: Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population

Fig. 2

In the least absolute shrinkage and selection operator (LASSO) model, the minimum standard was adopted to obtain the value of the super parameter λ by tenfold cross-validation. The λ value was confirmed as 0.104 (log(lambda): − 2.262), where the optimal lambda resulted in 6 nonzero coefficients. A Six risk factors selected using LASSO regression analysis. Solid vertical lines were drawn at the optimal values using the minimum criteria (red line) and the 1 standard error of the minimum criteria (black line) (at minimum criteria including Age, DLCO, RVD, CRP, Albumin and Globulin). B LASSO coefficient profiles of the 95 risk factors. Abbreviations: RVD, right ventricular diameter; DLCO, diffusing lung capacity for carbon monoxide; CRP, C-reactive protein

Back to article page