Sentence examples for conversion prediction from inspiring English sources

In this survey, we performed three different meta-analyses for evaluating the accuracy and effectiveness of diagnostic tests (i.e., FDG or amyloid), in order to make a judgment about quality of evidence (GRADE) on the early or differential diagnosis and for conversion prediction of dementia in our population.

Scientific evidences available regarding each of the tests (F-FDG-PET or amyloid-PET) for the early and differential diagnosis of AD, as well as for MCI conversion prediction, are graded in terms of Level of Confidence (LoC: VL = very low, L = low, M = moderate, and H = high), as reported by GRADE system [ 74– 76].

The root mean square error in the verification of conversion predictions for the larger scale photocatalytic reactor when compared with experimental data is less than 5.6%.

If you shape the objective function of your predictive model to be optimizing for lifetime value as opposed to conversion, then that prediction can be used all the way down the funnel to help customer success teams load-balance customers.

The optimized values of toluene conversion obtained via prediction model and experimentations at 240 °C were 92.7% and 92.1%, respectively.

In the approach, the interdependence structure was summarized by a unique covariance matrix through the conversion of the prediction errors to a multivariate Gaussian random vector.

The explanation for this anomaly may be the decreased functional connectivity observed between the right temporoparietal junction and sensorimotor areas in the conversion tremor condition if predictions do not reach the right temporoparietal junction, they cannot generate prediction errors.

Besides, the reactor model elucidates the importance of accounting for the role of the hydrodynamics on the heat transport in order to have reliable conversion and yield predictions.

Recent experiments on low-temperature oxidation of dimethyl ether (DME) at atmospheric pressure reveal much lower fuel conversion than the predictions of all published models.

The conversions obtained by prediction from the model were linearly correlated with the experimentally obtained values with a slope of 0.9488 and an R 2 -value of 0.9488, indicating that the model is able to fit the experimental data fairly well.

Predicted = prediction of PA based on the conversion of one brand to the other using a conversion equation.