Top 15 predictors for machine learning algorithms with a built-in importance measure.

Ranking of the top 15 predictors for the four models with a built-in importance statistic demonstrates considerable overlap in the top predictors for each model. Furthermore, nearly all of the markers found to best discriminate CDR 0 from CDR>0 participants in the more targeted ROC analyses (Table 5) were also identified as the top predictors in the machine learning models, reconfirming their biomarker potential.针对内置重要性统计量的四款机器学习模型，其前15个预测因子的排名结果显示，各模型的核心预测因子存在显著重叠。此外，在更具针对性的受试者工作特征（Receiver Operating Characteristic，ROC）分析（表5）中，被发现可最优区分临床痴呆评定量表（Clinical Dementia Rating，CDR）评分0分与CDR评分>0分参与者的几乎所有标志物，也均被上述模型识别为核心预测因子，再次证实了这些标志物的生物标志物（biomarker）潜力。