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We evaluated the predictive performance of MIRS using 100 protein ligand complexes and their binding affinities.
We evaluated the predictive performance and clinical utility of a published population pharmacokinetic model of infliximab in children with CD.Within a cohort of 34 children with CD who had infliximab trough concentrations measured, the pharmacokinetics of each patient was estimated in NONMEM® using a published population pharmacokinetic model.
First, we evaluated the predictive performance of the proposed parameters in the literature when jointly and nonlinearly combined.
The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases.
In order to decide on cost and γ for SVM RBF we used data from the logD dataset; a training set of 5000 chemical structures together with a test set of 50,000 structures, and evaluated the predictive performance of the models for varying cost and γ.
Firstly, we evaluated the predictive performance of IgC2N on simulated data.
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To evaluate the predictive performance, we calculated the prediction mean-squared error for regression and the error rate for classification.
In order to evaluate the predictive performance of models predicting log Vss, the Vss-target dataset was randomly divided into two sets.
24 To evaluate the predictive performance of the retrieved prediction models, we used the original prediction models (regression coefficients with intercept or baseline hazard) as published.
Receiver operating characteristic analysis was performed to evaluate the predictive performance of MR-proADM, CT-proET-1, MR-proANP, and CT-proAVP.
To evaluate the predictive performance of the classification method, we performed a cross-validation experiment using the gold standard compound protein interaction data.
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