Fig. 2
From: Metabolite changes in blood predict the onset of tuberculosis

Machine learning models (biosignatures) discriminating between progressors and controls. Panels show receiver–operator characteristic (ROC) curves. The three panels correspond to the three models tested: a, model Total which was generated using all training set samples; b, model Total/Baseline which was generated using only BL training set samples. Model evaluation was stratified by time to TB diagnosis: all, evaluation on all test set samples; proximate, evaluation on test set samples collected < 5 months before TB diagnosis; distal: ≥ 5 months. c Results of enrichment test on metabolites ordered by their importance in the Total and Total/Baseline models. The metabolite sets correspond to biochemical groups and clusters of metabolites identified previously in TB patients. Color intensity corresponds to p-value, and symbol size corresponds to the strength of the enrichment. P-values were corrected for multiple testing, and AUC was used as a measure of effect size