Convergence of the algorithm (average performance differing less than 5% from that of the bestperforming individual) was found after 50 generations for each independent run. This finding affirmed that the selected maximum number of generations was appropriate for this problem. Additional parameters of the evolutionary algorithm were set to their default values as suggested by the InSyBio Biomarkers tool user manual (arithmetic crossover probability: 0, mutation probability: 0.01, two-point crossover probability: 0.9). Stratified 10-fold cross-validation was used to train and test the prediction models. Further details on the implementation of the trained models and a summary of the performance metrics used are available in the Supplementary Data.