Sentence examples for no classifier could predict from inspiring English sources

For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain.

A leave-one-out procedure with cross-validation was used to determine how well this classifier could predict whether an individual was conservative or very liberal when trained on the other participants' data (see Experimental Procedures for full details).

We investigated whether a blood-based gene expression classifier could predict response to a targeted biologic therapy in RA when subjected to statistically rigorous evaluation across multiple patient cohorts.

The fact that our classifier could predict which sound was heard or imagined means that our results go beyond previous studies demonstrating an overall activity increase in early visual cortex in response to auditory stimulation [ 20] or visual mental imagery [ 17, 18].

Next, we investigated whether the derived classifiers could predict cancer status of post-treatment samples with evidence of active disease (determined by CA125 serum levels >30) at the time of sample draw (47 samples).

All of these three classifiers could predict a child's asthma control deterioration one week ahead with reasonable accuracy.

This analysis was initially unsatisfying, as no classifier could reliably distinguish chromosomal from non-chromosomal proteins.

For RNA-binding site prediction, Terribilini et al.[ 3] reported a Naïve Bayes classifier that could predict at 38% sensitivity and 93% specificity (65.5% prediction strength).

We hypothesized that the expression of the mitogenic classifier genes could predict the mitogenic outcome of other insulin analogues.

The metabolic profiles, colonoscopy outcomes, and medical histories were then analysed using machine learning to create a classifier that could predict whether a future patient requires a colonoscopy.

With this method, we were able to develop and validate a gene classifier that could predict which patients with ER+ BC were at high risk of relapse despite tamoxifen treatment.