Exact(1)
**P values for linear trend obtained by incorporating the variable as linear term in Cox regression models.
Similar(59)
By incorporating the categorical variable of fusion types Fx (III, IV, ETS) with log-transformed continuous variables of PCA3 and serum PSA, a logistic regression model was developed to calculate an individualized molecular score for optimal prediction of biopsy outcomes (Table 5).
The projected controller setup cancels all possible nonlinearities by converting the entire PV system into two decoupled linear subsystems with stable internal dynamics by incorporating the control variable 'S'.
P value for trend was estimated by incorporating the categorical variable as a linear term in linear regression models.
Moreover, by incorporating the categorical variable of Fx (III, IV, or ETS) with urine PCA3 and serum PSA, the multivariate FPP model not only has an overall predictive accuracy of 77% to overall prostate cancer detection, but also allows individualized stratification of prebiopsy patients into distinctive risk groups.
The governing partial differential equation of the system is converted to nonlinear systems of simultaneous ordinary differential equations by incorporating the similarity variables.
We penalize the violation of soft constraints by incorporating the relaxation variables to the objective function.
The P value for trend was estimated by incorporating the background variables as linear terms in the regression models.
We obtained P for trend by incorporating the categorical variables as linear terms into the Cox regression models.
We then extended the model by incorporating the smoothed weather variables.
There he proposed to improve deterministic models for the 'climate' (slow variables) by incorporating the influence of the 'weather' (fast variables) in the form of random noise.
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