Sentence examples for implemented probabilities from inspiring English sources

Based on implemented probabilities, these decision items influence the further treatment procedures.

Depending on the NYHA class of the patient, the implemented probabilities for decisions regarding different events in the model change.

A worsening of the patient's health condition, which is reflected by implemented probabilities with regard to the severity of heart failure, is the first decision-step for further treatment procedures.

Based on the observations of FDR significant covariances between traits in 0.52% of our bivariate analyses and in 21% of multivariate analyses, we implemented probability calculations to predict a range of values for the number of traits affected by a single putative pleiotropic mutation.

Difficulties experienced in implementing probability-based limit states design criteria for earthquake are summarized.

In this paper we (1) review previous works on using GPUs for non-graphics applications, (2) implement probability-based simulations on the GPU, namely the Ising and percolation models, (3) implement vector operation benchmarks for the GPU, and finally (4) compare the CPU's and GPU's performance.

An important outcome of these studies is the notion that neurons in parietal and frontal regions accumulate evidence over time until a given decision criterion is reached (rise-to-threshold mechanisms), fuelling the idea that these neurons implement probability "reasoning" to emit a verdict about the state of the world.

Ding et al. [ 17, 18] implement probability of single-strandedness, when the weighted ensemble of likely structures is taken into account, as an accessibility criterion.

Then, any voting strategy (sigma _4^{EA}) that guarantees that policy E is implemented with probability 1 is a best response.

In the present work, authors have implemented normal probability plot to perform normality test in Microsoft excel, 2007.

However, we implemented inverse probability censoring weighting to account for differences in measured characteristics between the baseline and follow-up samples.