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The overall estimated FDR for the first and second validation sets were 2.53% and 9.21%, respectively.
The validations sets had sensitivities of 86.7% and 80.2%, specificities of 91.4% and 87.7%, precisions of 91.1% and 87.4%, accuracies of 89.0% and 83.8% and F-measures of 0.89 and 0.84 for the first and second validation sets respectively.
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This correlation was significant for the first and third validation sets (P = 0.003 and P = 0.04), and borderline significant for the second set (P = 0.07) (Figure 3).
We present extensive numerical validation for the third and fourth order cases with Lagrange finite elements.
The rule was mainly clinically relevant for the patients from the development and first validation populations.
We only included initial derivation and first validation studies for the scores identified.
The SDEP is 0.57 for all the compounds, and 0.69 for the second validation set.
A 10-fold cross validation led to a choice of 8 variables (probes) for the first dimension, around 100 for the second and 70 for the third dimensions.
For the MAP-Tau cohort, we employed 10-fold cross-validation for the first layer and Monte-Carlo cross-validation for the second.
Models fitted to the first data sets were applied for the second, validation data sets.
The first 50% was used for training, the second 25% for validation, and the remaining 25% for testing.
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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