<p><b>A.</b> Summary of the false and true positive rates of the 29-gene panel in classifying CRC cases. <b>B.</b> Summary of the false and true positive rates of the 29-gene panel in classifying AP cases. Analyses were performed using 500 bootstrap validations. The boxplots represent the distribution of the 500 bootstraps. The black line represents the average values over 500 bootstraps for clinical specificity and sensitivity.</p
<p>The area under the ROC curve (AUC) represents how accurate the individual and combined biomarkers...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (R...
<p>*ROC plot for diagnostic accuracy presents true positive rate vs. false positive rate (or sensiti...
We compute the area under the curve (AUC) for each model and each cohort, where a perfect classifier...
<p>The ROC curve was generated using the results obtained by analyzing 50 negative human serum sampl...
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>Receiver operating characteristic (ROC) analysis showing the discrimination of healthy controls (...
ROC (i.e. receiver operating characteristic) curve (thick continuous line) from the leave-one-family...
<div><p>ROC analysis included 136 patients with no myocardial injury as a negative group and 16 pati...
<p>The ROC analysis and curves are shown comparing between ACCP- and early RA subjects for all mRNAs...
<p>Receiver operating characteristics (ROC) curve of anti-SS-B titers for the diagnosis of connectiv...
<p>(A,B) ROC analysis of lung cancer patients and healthy controls, and healthy controls as a negati...
<p>The ROC curve showing the tradeoff between the True Positive Rate (sensitivity) and the False Pos...
<p>A receiver-operating curve (ROC) was generated as a preliminary estimate of the accuracy of relat...
<p>The area under the ROC curve (AUC) represents how accurate the individual and combined biomarkers...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (R...
<p>*ROC plot for diagnostic accuracy presents true positive rate vs. false positive rate (or sensiti...
We compute the area under the curve (AUC) for each model and each cohort, where a perfect classifier...
<p>The ROC curve was generated using the results obtained by analyzing 50 negative human serum sampl...
<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evalua...
<p>Receiver operating characteristic (ROC) analysis showing the discrimination of healthy controls (...
ROC (i.e. receiver operating characteristic) curve (thick continuous line) from the leave-one-family...
<div><p>ROC analysis included 136 patients with no myocardial injury as a negative group and 16 pati...
<p>The ROC analysis and curves are shown comparing between ACCP- and early RA subjects for all mRNAs...
<p>Receiver operating characteristics (ROC) curve of anti-SS-B titers for the diagnosis of connectiv...
<p>(A,B) ROC analysis of lung cancer patients and healthy controls, and healthy controls as a negati...
<p>The ROC curve showing the tradeoff between the True Positive Rate (sensitivity) and the False Pos...
<p>A receiver-operating curve (ROC) was generated as a preliminary estimate of the accuracy of relat...
<p>The area under the ROC curve (AUC) represents how accurate the individual and combined biomarkers...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (R...