Table 1. Hyper-parameters, OBB, ROC-AUC, and confusion matrix of the trained random forests model.

Donor (no. of data points)	ntree	mtry	OOB (%)	ROC-AUC	TP	FP	FN	TN
All donors – full FoV (36)	100	2	16.67	0.944	16	2	4	14

ntree, number of trees; mtry, number of variables selected for the best split at each node; OBB, out-of-bag error; ROC-AUC, area under receiver operating characteristics curve; TP, true positive; FP, false positive; FN, false negative; TN, true negative.