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We exploit two different ways of normalizing data: standard deviation and individual normalizations.
So we experimented with two different ways of normalizing data: standard-deviation based and individual normalizations.
Possible influence by different experimental batches or cohorts were controlled by statistical analysis using batch variables or normalizing data with Succinate dehydrogenase [ubiquinone] flavoprotein subunit (SDHA), one of endogenous controls.
On the one hand, there are the technical challenges of gathering and normalizing data inputs — the act of making different types of data comparable — connecting them to a unified view of the customer, and then aligning the AI-driven decisions to real-world actions.
Normalizing data is a big challenge for developers.
Normalizing data from different ways of partitioning the same population will provide incompatible conclusions about the associations that hold in the total population.
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By normalizing, using data from a normal population, mfERG measurements are more comparable and in reasonably close agreement across instruments, and the effects of differences in instrumentation are minimized.
Only the Q normalization method, which is an appropriate method commonly used for normalizing microarray data [ 23, 24], exhibited any substantive differences.
A relatively simple metric for normalizing rotation data from disparate girder designs is also introduced and recommended for consideration in any future connection rotation demand benchmarks.
There was small, but significant differences in all FHA parameters between genders and normalizing positional data relative to epicondylar width helped to reduce this difference.
Relative regional glucose metabolism was determined by normalizing (18F FDG data to the whole-brain uptake.
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