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Subsequent analysis using the verification data set confirmed the association between index and PML, with a significantly higher index distribution for pre-PML samples from PML patients than for samples from non-PML patients (median = 2.3 vs 1.9; p = 0.0199; see Fig 1B).
The next one is used as verification data set.
The verification data set consisted of 1,483 non-PML anti-JCV antibody positive MS patients (baseline samples) and 26 MS patients who developed PML from STRATIFY-2.
The median exposure to natalizumab at the time when the lowest index was obtained in the non-PML population was 19 infusions for the test data set, 23 infusions for the verification data set, and 21 infusions for the combined data set.
A similar relationship was observed for the verification data set (see Fig 3B) and the combined data set (interaction p = 0.0158; Fig 4A).
Figure 4 shows the Genstruct® Technology Platform heatmap key for Figure 6, Figure 7, and 8. Figure 6 and 7 show the RCR-predicted hypotheses from the four verification data sets which were present in the literature model.
The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay.
Even though the 11 MSH6 variations do not compose an ideal data set for the verification of the three-step model in assessing VUS pathogenicity, the importance of the interpretation of tumor IHC data prior to the identification of the VUS taken for further assessment is highlighted.
"It's a valuable data set".
This will improve the original remote sensing-based stratification by providing a field training data set for remote sensing image analysis and ground verification.
In a single simulated data set, varying false negatives from 0too 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com