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A more elegant method with greater sensitivity would be preferable.
Compared with classification methods used in previous studies [ 18, 25], SVM is a statistical learning method with greater accuracy in diagnostic ability [ 32, 33, 54, 56] and with more consistent performance at our sample size [ 57].
The selection of specific imputation methods for genomic selection analyses were restricted to the method with greater GS accuracies within the same percentage of missing data class (i.e., 30% vs. 60%).
Making full use of high-density SNP genotyping and haplotype frequency (i.e., LD) information derived from population data or reference databases (such as HapMap), it becomes possible to construct a method with greater power and resolution in identifying ancestral haplotypes, which requires neither pedigree structure information nor genotype data on family members (e.g., [Sham et al., 2009]).
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Harris applied this method with great destructive effect in Germany—most notably in the firebombings of Hamburg and Dresden.
So the statistic method is regarded as the dominant method with great potential application in practice.
The flexible and variable testing conditions provided the new method with great potential.
Resting-state functional magnetic resonance imaging (rsfMRI) is a translational imaging method with great potential in several neurobiologic applications.
In this paper, we improved our previous in situ refractive index method with great temperature-controlled capability.
The advantages in the time of detection and ease of process endow this method with great potential in clinical usage, especially mass epidemiological screening.
We have been implementing the method with great success for the past five years in the US, Europe, Israel, and even Australia.
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