Fig. 1.

Schematic representation of the Leave-One-Monkey-Out approach used for the machine-learning algorithm for biomarker discovery. Each monkey is used as the independent test data in an iterative manner and is thus “left out” of the samples on which the machine-learning model is developed. One stability run is defined as a single loop where each monkey is left-out once