Sentence examples for outcome labels from inspiring English sources
The predictive accuracy for the samples with nine poor outcome labels was only 45% for DMFS and 36% for BCSS (see Figure 4 and Additional data file 4).
We found significant enrichment for univariate association with recurrence in these 138 genes (see Additional file 8, Figure S1 for comparison of the distribution of nominal p-values with a null distribution empirically determined by permutation of the outcome labels).
The assumption of sample independence is violated in cross-validated predictions, so following Simon et al. (2011), we also assessed significance for the Elastic Net model by permuting the outcome labels 500 times.
Through the repeated permutation of clinical outcome labels and the re-computation of mutual information values, a threshold θ is defined as the maximum of the average mutual information values for each gene pair.
Furthermore, while we used 'death' as the outcome variable for the prognosis prediction described above, we find that it is robust to using other variables as outcome labels (Additional file 2: Supplementary Notes).
To control for this, the data were re-analysed 999 times using random permutations of the patient outcome labels to generate true (permuted) P-values for each gene set.
The strategy for building the detection algorithms is transferrable to other data environments where explicit outcome labelling such as the final diagnosis is available.
We now only consider the subset of SNPs X ˜ obtained from L after neglecting all irrelevant SNPs and use a measure correlation function χ2 X ˜, Y) to test the association between the outcome label and each SNP X j.
Statistical entropy is derived from the negative binomial distribution where an experiment with two equally likely outcomes, labeled success or failure, is considered.
Previous analyses of patient-reported outcome (PRO) label claims concentrated only on successful label claims.
Label C0 indicates that the patient is normal (negative outcome) while label C1 indicates that the patient has abnormal CT scan (positive outcome).
