Sentence examples for be ideal to predict from inspiring English sources

Thus, it would be ideal to predict therapeutic efficacy for each patient before treatment is initiated.

Specific markers for heart and/or coronary dysfunction may therefore not be ideal to predict the outcome of patients with acute dyspnea in the ED.

Specific markers of the cardiovascular system like natriuretic peptides may therefore not be ideal to predict the outcome of patients with acute dyspnea in the ED.

Several authors have highlighted the problem of early failure, which may span from 20 to 60% [ 34]; in promoting fistula placement and use, it would be ideal to predict which patients would benefit from a fistula that would mature successfully.

It is ideal to personalize medical treatment for individual RA patients by predicting efficacy and safety of a given biologic.

Performing CFD analysis using sensor data as input would be ideal for predicting construction site thermal environments, but CFD analysis typically requires from several hours to several days.

Although studies with receptor knockouts or local injection of TNF-α can give mechanistic insights, they may not be ideal for predicting the effects of etanercept treatment.

Since the relation between exhaled breath metabolites and blood glucose levels shows high inter-person variation, a cross-sectional design may not be ideal for predicting glucose levels using breath metabolites.

It would be ideal if one could predict objectively the modulation of this ratio based on a predictive in silico platform.

As serum-based biomarkers are easily accessible, cheap and can be determined in serial measurements, they are ideal tools to pretherapeutically predict the therapy outcome enabling an effective patient stratification for SIR treatment and to monitor local and systemic biochemical SIRT effects when determined repeatedly during the very early phase after SIRT application.

However, false alarms in cancer screening and security are costly, thus it would be ideal if our measures predicted an increase in hits without a corresponding increase in false alarms, which was the imperfect experimental solution to the low prevalence effect (Wolfe et al., 2007).