Sentence examples for introduction of prediction from inspiring English sources

The introduction of prediction schemes enables to minimise the number of dropped user requests for both classes of mobile devices.

The novel approach used in this study is the introduction of prediction models, rather than the use of fixed cut-off levels for LBC or L/S ratio.

However, it is reasonable to suppose that, in some cases, clinicians will want to be sure that introduction of prediction model has a low chance of leading to inferior patient outcomes.

In a before-after study, pregnant women with preeclampsia or HELLP syndrome in their previous pregnancy receiving care as usual (before introduction of the prediction model) will be compared with women receiving recurrence risk guided care (after introduction of the prediction model).

The PreCare study uses a before-after design, in which outcomes and costs before the introduction of the prediction model (i.e. care as usual) are compared with outcomes and costs after introduction of the prediction model (i.e. recurrence risk guided care).

Therefore, the introduction of the prediction functionality in the load balancing of the decision-making requests is expected to enable the proactive management of such requests, improving the network management procedure.

Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes.

A prominent example is the introduction of numerical weather prediction (NWP) and the use of ensemble prediction systems (EPS) over the last decades (Hirschberg et al. 2011; Wernli 2012).

Evaluating the performance of a prediction model in datasets not used in the derivation of the prediction model (external validation) is an invaluable and crucial step in the introduction of a new prediction model before it should be considered for routine clinical practice [ 12, 13, 26, 35].

Introduction: Early prediction of neurological outcome of post-anoxic comatose patients after cardiac arrest (CA) is challenging.

This paper investigates the introduction of an LMS prediction-error filter (PEF) as a prefilter to the equalizer and demonstrates that it reduces the convergence time of the two-stage system by as much as two orders of magnitude.