Sentence examples for measures were sensitivity from inspiring English sources

Main outcome measures were: sensitivity, specificity, positive and negative likelihood ratios of the primary studies, weighted means of these parameters in each comparison (clinical examination, radiography, and ultrasound compared to a reference standard in diagnosing AMS), and summary ROC curves and their Q* points where sensitivity equals specificity.

The main outcome measures were sensitivity, specificity and positive predictive value (PPV) for each criterion.

Reported diagnostic performance measures were sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−), and the diagnostic odds ratio.

Main outcome measures were sensitivity and specificity of PCR in the detection of fungus in corneal keratitis.

The quantitative measures were sensitivity, specificity, positive and negative predictive values (PPV and NPV) and the area under the ROC curve (AUC).

Other diagnostic measures were sensitivity 62%, specificity 92%, positive predictive value 67%, negative predictive value 90%, accuracy 85%, positive likelihood ratio 7.3 and the negative likelihood ratio 0.42.

The primary outcome measure was sensitivity for detection of influenza A and B, respiratory syncytial virus, parainfluenza 1 3, and adenovirus.

The best accuracy of the SigFlux measure is sensitivity 85%, specificity 73% while that of the betweenness centrality is sensitivity 50%, specificity 68% (both for a threshold of 0.1).

Outcome measures were insulin sensitivity (indexed by quantitative insulin-sensitivity check index [QUICKI]) and fasting plasma lipid profile.

The primary outcome measures were the sensitivity and specificity of residents using ultrasound to distinguish pneumothorax from normal lung on the cadaver model.

Secondary outcome measures were the sensitivity and specificity of symptoms of influenza for identifying laboratory confirmed cases and the completeness and timeliness of contact tracing.