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Although reasonably good prediction performance was obtained from the QSAR models, the prediction gave no insights into the detailed mechanism of actions.
However, Fig. 20 shows that despite having the least R2 among the ANN models, the prediction errors are low and consistent over the values except at the highest extreme.
Thus, when researchers assume that there will be measurement invariance across countries and then, during data analysis, use the scaled latent indices as predictors in the country-specific prediction models, the prediction coefficients across countries will only be the same under very restricted conditions.
Under both models, the prediction accuracy for BrS remains inferior to that of LQTS, because of limited data.
Consistent with the PLS-2CV models, the prediction was only valid with EA-GC-MS data-set (Table 7).
To determine the BRCA mutation prediction capability of the Claus, Frank, Gilpin, Evans1 and Evans2 models, the prediction scores were determined for 263 families with breast and/or ovarian cancer patients and compared to the mutation status of these families.
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For the gerbil threshold model, the prediction was best if the two preceding years were included.
On the basis of this model, the prediction value was calculated followed by ROC curve analysis.
In this parametric model, the prediction errors were fully signed and varied across trials and subjects.
The top 100 genes were included in a multivariate Cox model as the prediction model.
In order to evaluate the coherence of the two types of models, the forward prediction model and the backward prediction model, we used the predictions of the forward prediction model as an input to the backward prediction model and compared the resulting predicted values with the actual values.
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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