However, we do note that the cut-points identified at each partitioning stage using the test cohort were not replicated as significant discriminators using the Fisher's exact statistic in the validation cohort.
For each analysis, optimal cutoff points for prediction of remission status were first identified using the test cohort, following this, the performance of these cutoff values was assessed in the validation cohort using the binomial test.
Differential expression was defined as fold change (FC) > 2 with FDR corrected (Benjamini Hochberg) p-values <0.05 All the pilocytic astrocytomas used in the test cohort contain the KIAA1549-BRAF fusion that activates the ERK/MAPK pathway.
As per the analysis plan, the first 50% of the MDD participants who completed imaging at baseline visit were used as the test cohort (n = 102) and the second 50% of the MDD participants as the validation cohort (n = 102) (Grieve et al., 2013b).
Using this cut-off value, the test cohort was separated into low-expression and high-expression groups (15 and 23 cases, respectively).
This is particularly relevant for the test cohort used in microarray experiments.
Both systems, the age-independent classifiers and the age-specific classifiers, were used to classify independent data from the test cohort of 71 recordings, with the results shown in tables 7 and 8.
First, using a test cohort of 32 patients, we observed that LV dysfunction after MI (4-months EF < 40%) had a biosignature in blood cells in the acute phase.
Similar results for the combination of hippocampal subfields and total hippocampal volume were obtained when using the ADNI cohort as the test set and the AddNeuroMed cohort as the training set (Table 5).
For the combination of hippocampal subfields, using the AddNeuroMed cohort as the test set and the ADNI cohort as the training set resulted in a similar classification accuracy, 82.1 % (sensitivity = 77.1 %, specificity = 86.9%%, AUC = 0.90) compared to 81.1 % for total hippocampal volume (sensitivity = 75.2 %, specificity = 86.9%%, AUC = 0.897).
One cohort was designated the training cohort, and the second, termed the testing cohort, was used to corroborate the results from the training cohort using quantitative, real-time PCR (qRT-PCR).
