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None of these predictors made it to the final selection of most important predictors.
These predictors made predictions by ranking and combining a number of internal and external models via a novel global local model combination algorithm.
The results as shown in the table indicate that, two out of the eleven predictors made statistically significant contribution to the model (insurance status and financial difficulties).
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Cutoff values were chosen for all continuous variables to simplify predictors, making them easier to enter into models utilized in a busy clinical setting (Table 2).
In my opinion, these constraints coupled with the lack of patient stratification by HCC predictors, make the evaluation of the prophylactic activity of IFN and NUC even more difficult.
However, the readily available predictors make the model easily applicable.
De novo predictors make up the final category of motif resources.
So yes, the predictor made by new Hunch employee Ben Gleitzman (a former Googler) is very accurate.
The median human predictor made 21 correct predictions and achieved an AAE of 0.732 log S units, both better than any individual.
A large training-validation study is needed to construct a robust predictor made up of multiple factors in which cfDNA might play a central role.
The relative contributions of predictor variables in the final regression models were determined by the proportionate contribution that each predictor made to the regression model multiple R using the Pratt index (Pratt 1987).
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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