ROC analysis and calculus of sensitivity, specificity and predictive values.
收藏NIAID Data Ecosystem2026-03-07 收录
数据链接：
官方服务：
资源简介：
AUC: area under the curve, FPF: false positive fraction, TNF: true negative fraction, TPF: true positive fraction, FNF: false negative fraction, PPV: Positive predictive value, NPV: Negative predictive value. aOptimal cut-off values (ng/ml) were selected according to the ROC analysis. bChi square test. cJ = sensitivity+specificity − 1.
创建时间：
2013-02-06
