CEACAM5 and colorectal carcinoma: At the population scale, machine-learning classifiers trained on extracellular-vesicle miRNAs can extract compact signatures with strong discrimination: in the FEVOR project, a gradient-boosting model using fecal EV miRNAs identified a 15-miRNA signature that recognized stage 0-I CRC with an area under the ROC curve (AUC) of 0.94 (where 0.5 indicates no discrimination and 1.0 is perfect), outperforming CEA and CA19-9 measured in the same context [123].