Sentence examples for estimated ris from inspiring English sources

For those with smaller numbers such as cancers of liver and pancreas, the estimated RIS smoothes the curves for the observed RIS, also showing a very good fit.

To estimate Ris directly (without reference to a control sample), the unknown (NCq A/ NCq B-term preseNCq A/ NCq B-term.

The Middle-East market for PACSs-RISs was estimated at $86 million in 2009 and could grow to $140 million by 2014 [ 13].

More importantly, estimating errors of Ris is simpler as detailed in later sections and Appendix S1 section 2. Thus, the formula for the regression equation is: <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0011723.e006.PNG" class= inline-graphic"/> With α and β being intercept and slope, respectively.

Instead Ris can be estimated as a difference of regression estimates (from Eq. M.2): <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0011723.e009.PNG" class= inline-graphic"/> The benefit of using regression estimates is that simple statistics can be applied to determining errors of LOG (Ris) (see Appendix S1 section 2).

Using Eq. R.1, LOG (Ris) can be estimated as: <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0011723.e010.PNG" class= inline-graphic"/> A prerequisite is that αs and βs are constant between interest and control samples for each target.

Time to relapse for the OLZ-RIS and RIS-OLZ groups was estimated using Kaplan-Meier survival curves, and also analyzed using Cox-proportional hazards model controlling for patient characteristics.

The present study estimated the LRLs of quantitative cord G6PD using standard statistical methods endorsed by the IFCC-CLSI for establishing RIs [ 24, 25].

5) Estimate estimated.

Thus, NBV and lesional-WM MTr values entered a penalized multivariate logistic regression analysis, to estimate a multiparametric score giving the probability for a RIS subject to be RRMS patient or HC (Figure 5A and B).

In order to estimate cancer death distribution for regions where little cancer mortality data is available (AfrD, AfrE, AmrD, EmrB, EmrD, SearB, SearD, WprB1, WprB2 and WprB3 sub regions), we developed an age-period-cohort multiplicative model for the relative interval survival (RIS) for each site.