Figure 6.

Cross-validation of common prediction model for TG and FFAs during lipid infusion. For cross-validation of TG and FFA common prediction models, data were randomly separated into a training set (90% of data points, top panels), on which predictive algorithms were built, and a validation set (remaining 10% of data points, bottom panels), on which algorithms were applied. Correlation coefficients and root mean square errors (RMSE) were comparable between the training sets (A) and validation sets (B).