The meta-analysis utilized the Wilcoxon signed-rank test to identify the optimal features set. The F1-score was the primary metric to compare the performance among 16 molecular feature sets. The evaluation results are detailed in S1 Table (Supporting information), while the summarized comparison is illustrated in Fig . Therefore, RDK7 was selected as the optimal molecular feature to develop a machine-learning model.