Sentence examples for ideally predict from inspiring English sources

Biomarkers that measure the stages and phenotypes of OA and, ideally, predict risk of joint-related outcomes would significantly improve decision-making in terms of dosing, treatment time, risk/benefit ratio, and transfer knowledge to label.

However, a prognostic assay would ideally predict mortality with both high sensitivity and specificity based on a single criterion to avoid the uncertainty associated with non-extreme scores.

A perfect scoring system may not exist, but it should ideally predict both 30-day mortality and the requirement for mechanical ventilation or vasopressor support.

In the example presented, the percentage of children with the dose ideally predicted (± 20%% of actual dose) increased from 41 % with a priori prediction to 70%% with a posteriori revision of warfarin maintenance dose.

Ideally, to predict the efficaciousness of anti-TB drugs it would be desirable also to predict the concentrations within the granulomatous regions that develop during TB infection and to link these to pharmacodynamic models describing the effect of the drugs on bacterial levels.

Ideally, the predicted score should be equal to the true score.

Ideally, the predicted <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0007492.e042.PNG" class= inline-graphic"/> should be close to the true one and the predictive performance of the training based on HPRD in vivo interactions should be the same for both, common and unique interactions.

Ideally, the predicted y should be close to the coded class values, such as organized in the range rather than stochastically assigned.

Ideally, if predicted and observed 5-year survival probabilities agree over the whole range of probabilities, the plots shows a 45° line.

Ideally the predicted risk equals the observed incidence throughout the entire risk spectrum and the calibration plot follows the 45° line.

We present GimmeMotifs, a de novo motif prediction pipeline ideally suited to predict transcription factor binding motifs from ChIP-seq datasets.