Fig. 2.

Heatmap summary of cross-validation performance for all candidate models. The feature selection/machine-learning combinations with the highest averaged area under the curve (AUC) across validation folds (from 20 repeats × 5-fold cross-validation) are highlighted with bold yellow cell border lines. These best-performing models were selected for internal independent and external cohort testing. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)