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Heat map of models trained on different datasets and evaluated on testing datasets. Each model is evaluated on three different testing datasets. The performance is assessed using the following metrics: (A) sensitivity (SN), (B) accuracy (ACC), (C) area under the receiver operating characteristic curve (AUROC), (D) Matthews correlation coefficient (MCC), (E) F1-score, and (F) the area under the precision–recall curve (AUPRC).
