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The Phenomena of Interest and Context model 10 underpinned the categorisation and construction of search terms, and as such, the full range of study methodologies and potential interventions were of interest.
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In this section, details of the proposed methodology and potential improvements are given.
Section 3 presents the data used and the methodology and potential econometric difficulties, and Section 4 analyzes the results and provides conclusions.
The experimental data obtained are introduced into the formulated estimation methodology, and potential emissions of dust from PEO-admixed Na-mmt are determined.
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However, there is significant debate about how to evaluate the methodology and potential biases of the animal studies.
An important part of this debate is how to evaluate the methodology and potential biases of the animal studies in order to establish how confident one can be in the data.
The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics with a focus on upper gastrointestinal cancers are considered herein to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.
The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics as well as their limitations in gastrointestinal cancers are considered to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.
The aims of this review were to examine which pain measurement scales have been used in high quality acute pain trials, to investigate other common measurements or characteristics, to confirm that different scales used by standard methods give the same estimate of analgesic effect, to investigate remedication methodologies and the potential of 'time to remedication' as a standard outcome.
In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays.
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