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Each MRI variable was coded on two to seven different pathoanatomical stages (categories), as detailed in Additional file 1.
Because of the large number of cases and the inclusive nature of the NCDB, without restriction to certain stages, categories, or treatments, it is less subject to selection bias.
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For instance, miR169 targeted seven different CCAAT-binding transcription factors in the four stages (category 0 or 2) with very high abundance, but it also guided the slicing of three other non-conserved targets with very low abundance.
Models were run examining potential associations between MADRS and YMRS and menopausal stage categories (early vs. late/post), adjusted for study visit (where visit 1 was used as the referent category).
NLR further stratified patients within pT-stage categories.
Thirdly, there were nonsignificant segregations between certain adjacent stage categories using our proposed staging system.
Stage categories of disease at diagnosis were local/regional, distant, and unstaged.
The latter contains two staging categories: limited disease (LD) and extensive disease (ED).
In the selective-coding stage, categories were integrated to form a larger explanatory model.
Using the algorithm, 87.3% of cases could be assigned to one of the defined stage categories.
This system consists of two staging categories, limited and extensive disease (ED).
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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