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ROC曲线是用真阳性率(即敏感性)为纵座标,假阳性率(即1—特异性)为横座标作图所得的曲线,它可表示敏感性和特异性之间的相互关系。ROC曲线可用来决定最佳临界点(敏感性和特异性均较高,而假阳性和假阴性之和最小),或对2种或2种以上诊断试验的价值进行比较,帮助临床医师对诊断试验作出最佳选
The ROC curve is a plot of the true positive rate (ie, sensitivity) as the ordinate and the false positive rate (ie, 1-specificity) as the plot of the abscissa plotting the correlation between sensitivity and specificity. The ROC curve can be used to determine the optimal cutoff point (high sensitivity and specificity, with minimal false positives and false negatives), or to compare the value of two or more diagnostic tests to help clinicians diagnose Experiment to make the best choice