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On both sets, sensitivity, specificity, F1 measure, macro average and micro average were used as evaluation criteria.
Using a cutoff of scores <9 to indicate dissatisfaction showed fair discrimination in derivation (sensitivity 85%, specificity 80%) and validation data sets (sensitivity 75%, specificity 78%).
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Due to low amount of IgA in mucosal fluids, a high sensitive sandwich ELISA assay was set; sensitivity was enhanced by milk-based overcoating buffer and by a two-step biotin-streptavidin signal amplification.
They're useful for setting sensitivity if you don't use the on-the-fly (why wouldn't you?) but cut and paste or quick save and quick load would be just as good.
This is reflected in the difference between the validation set sensitivity (0.849) and specificity (0.882) shown for model logP2-1 in Table 1.
Note that the individual silicon crystals present due to the second deposition do not appear conductive because the current pre-amplifier setting (sensitivity = 1 nA/V) was adjusted to the magnitude of the current in the pit.
We evaluated model-set sensitivity and specificity using the Area Under the Curve [AUC] in a Receiver Operating Characteristic [ROC] analysis [81], [82], [83].
Using front of face ITIS for prediction of tympanic temperature ≥37.8°C, the area under the ROC curve was 0.86 (95%CI 0.75 0.97) and setting sensitivity at 86% gave specificity of 71%.
For the hepatobiliary set, sensitivity was 0.94 and specificity was 0.83, for the acute renal failure set sensitivity was 0.96 and specificity was 0.94.
For the acute renal failure data set, sensitivity increased from 0.69 to 0.89, with specificity 0.59.
At the set sensitivity of 95% and an ACS prevalence of 21%, the NPV was 96%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com