Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy

Figure 5 Screening of metabolic biomarkers via three machine learning algorithms. A and B: Least absolute shrinkage and selection operator regression model showed eight metabolites corresponded to the lowest binominal deviation; C: Support vector machine-recursive feature elimination model showed six biomarkers with the highest accuracy; D and E: Top 10 metabolites ranked by mean decrease Gini in the random forest model; F: Venn diagram revealing three shared metabolites in three algorithms.