Sentence examples for positive specificity from inspiring English sources

The specificity and sensitivity are calculated according to the following equations, respectively: Specificity = True negative True negative + False positive Specificity = True negative True positive + False negative.

By definition, sensitivity refers to the proportion of actual positives which are correctly predicted as positive; specificity is the proportion of actual negatives which are correctly predicted as negative; while PPV is the proportion of predicted positives which are actual positive.

When demanding all markers in the combination to be positive, specificity and accuracy increased but sensitivity dropped markedly.

MyDiagnostick AF classification in 6 out of the 139 recordings during sinus rhythm was considered false positive (specificity 95.9%95%5% confidence interval 91.3 98.1%).

MyDiagnostick AF classification in 6 out of 139 patients in sinus rhythm was considered false positive (specificity 95.9%95%5% confidence interval 91.3 98.1%).

Only 3 of the 18 individuals showed positive ENA results, and in all three the lone positive specificity was anti-chromatin.

We used the sensitivity (fraction of true positives) plus specificity (fraction of true negatives) as a classifier score.

When considering combinations positive only in case of all markers positive, specificities were increased compared to the single markers with decreased sensitivities.

Sensitivity is calculated as the number of true positives over the number of all positives; Specificity is the number of true negatives divided by all negatives.

To assess performance, Gimmemotif provides a ROC curve [ 26] that plots the number of true positives (sensitivity) as a function of false positives (specificity).

In addition to identifying the highest number of true binding events (sensitivity), a good peak caller algorithm is expected to produce the lowest amounts of false positives (specificity).