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The maximum specificity was observed for 'neurovascular involvement'.
At each cut-off value, maximum specificity was found with "two of two FITs+".
When maximum specificity was the prime goal ("AFS-spec"), we did not allow any mismatches during read mapping, and thus performed only a single mapping step with the highest stringency.
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Maximum specificity is observed for 17 features (specificity plot, red dot).
The median or mean of a negative control group is regarded an adequate measure for non-specific hybridization [ 13], however, due to low specificity (~50%) we conclude that neither thresholds should be used if maximum specificity is required.
The maximum average specificity was 0.59 for α-value of 0.000001, while the average sensitivities for the other α-values were the same as 0.94.
After comparison of the new derived system with the EWS as recommended by the UK's Department of Health, it was found that the cutoff point that gave maximum sensitivity and specificity was 3 (sensitivity and specificity of 0.63 and 0.72 vs 0.60 and 0.67, respectively) [[39]].
The score closest to the point with both maximum sensitivity and specificity was selected as the cut-off value.
The point at which the maximum difference in specificity was achieved increased with the strength of the baseline model, at which point the decrease in sensitivity with the addition of the new predictor was at its greatest.
The score having the closest distance to the point with both maximum sensitivity and specificity was selected as the cutoff score resulting in the greatest number of tumors being correctly classified as having or not having the clinical outcome.
For the regions with the highest AUCs, optimal cut-off points were determined to discriminate between the examined groups by locating the cut-off point where the distance from maximum sensitivity and specificity was minimal.
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CEO of Professional Science Editing for Scientists @ prosciediting.com