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From the recorded eye-movement data and known positions of lesions we extracted measures of visual attention and search.
We extracted measures of associations that were the most adjusted for sociodemographic and lifestyle factors, with and without further adjustment for adiposity measures.
Finally, for the extreme two levels of categorical ABR measures (e.g., highest and lowest income levels), we extracted measures of frequency (e.g., rates), or relative measures of association (e.g., relative rate [RR], odds ratio [OR], hazards rate ratios [HR]) and 95% confidence interval (CI), and p-values for linear trend where available.
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To investigate the discriminating power of the extracted measures, we built different SVM classifiers to distinguish PD patients from control subjects and trained each classifier using a different dataset of measures.
We have not actually created new notes within these extracted measures; the output Stream simply has references to the same objects.
For the SBM analysis, we utilized a semi-automated sulci delineation procedure, registered the brains to an atlas, and extracted measures of twenty four pre-selected regions of interest.
Calling the show method will, assuming correct setup of your environment, open a display of the extracted measures.
Ireland and South Korea extracted measures that set aside for their citizens a fixed number of the highly sought special visas for guest workers seeking to come to the United States.
The words of the extracted measures were then harmonized.
The extracted measures were categorised as either single-item or multi-item measures.
No single outcome has shown a benefit of FFP in > 50% of extracted measures.
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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