Sentence examples for predictors were applied from inspiring English sources
Several different cell line-derived drug response predictors were developed using the NCI-60 cell lines (http://dtp.nci.nih.gov/docs/cancer/cancer_data.html); however, when these predictors were applied to human data to predict response, the results were mixed [ 6, 7].
Values of the nine predictors were applied to the equation as described in Table 1: 1 for men and 0 for women; 1 for presence of antihypertensive drugs, lipid-lowering drugs, and smoker and 0 otherwise.
The following genomic predictors were applied to these data based on published methods: the good/poor prognosis signature of Van't Veer et al.[ 4, 5] that is currently the basis for the Mammaprint assay by Agendia, the recurrence score 21-gene assay that is the basis for Oncotype DX[ 6, 7], and the recurrence risk (ROR-S) and subtype predictions based on the PAM50 assay[ 8].
A complete tree with all branches is grown for each sample, and the predictors are applied to each branch [24].
A baseline predictor is applied to these, and the predictor is re-trained for the next time interval while including the newly introduced instances.
A multivariable version of the classical Smith predictor is applied to a double effect evaporator containing time delays in the control variables and some of the output variables.
Interestingly, the bitrate (per sample) as well as the ODG are improving as a function of the block size upon which the predictor is applied.
The first predictor is applied to the general form (1), whereas the second predictor is applied to the canonical form (5) after the first predictor has returned negative results (or to the general form (1) with (b= 0) or (b=2/(x+C)), where C is a constant).
This designed robust Smith predictor is applied to a reclaimer, which has a large output time-delay and is used in the raw yard of a steel plant.
The modified Smith predictor is applied to a reclaimer, which is used in the raw yard of a steel plant and has a large output time-delay.
Sites were classified as "conflict" or "no conflict", and a logistic regression model with ISS as predictor was applied to a random sample of 500 localities.
