Sentence examples for predictive sensitivities from inspiring English sources

That study showed that combining the SOFA scores with measurement of serum neopterin concentration (a specific cellular immune system activation marker) and tumour necrosis factor receptor 2 levels yielded the highest predictive sensitivities and specificities for pre- and postoperative outcomes [ 7].

In this we consider the models' predictive accuracy, predictive sensitivity to design parameters, versatility, computational efficiency, the reproducibility of predictions and software usability as well as the models' transparency (how open they are) and modularity.

Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident.

As shown in Table 3, while EEG-awakening, EEG-R, and sleep spindles all showed similarly high predictive sensitivity for awakening, only EEG-awakening had both higher specificity (84.5 %) and predictive accuracy (84.0 %), and its +LR (5.4) was also higher than that of EEG-R (3.3) and sleep spindles (2.8).

The predictive sensitivity and specificity of UbiPred [8] were 52.6% and 52.6%, respectively, indicating balanced predictive performance.

The predictive sensitivity and specificity of UbPred [9] were 42.1% and 68.7%, respectively, indicating poor sensitivity for an independent test set.

As presented in Table 2, the model that is trained using the combination of amino acid composition and PSSM profile of non-redundant fragment sequences of Ub sites performs best, with the best-balanced predictive sensitivity and specificity.

Independent test sets include 57 ubiquitylation sites and 3502 non-ubiquitylation sites, According to Table 3, are used to determine the predictive sensitivity, specificity, and accuracy of the proposed method, which were 57.9%, 72.4%, and 72.2%, respectively.

PC appeared to improve predictive sensitivity.

Evaluated by benchmark cross-validation, the predictive sensitivity and specificity of GPMiner are roughly 80%.

According to five-fold cross-validation results, the predictive sensitivity and specificity are both roughly 80%.