Sentence examples for model in discriminating from inspiring English sources

The usefulness of the newly-developed ESRF-specific model in discriminating between survivors and nonsurvivors among ESRF patients and non-ESRF patients was assessed using ROC curves.

The area under the ROC curve was 0.709, showing the fair accuracy of the model in discriminating between patients at medium-high or low risk of malnutrition.

The performance of each model in discriminating between patients and controls was assessed using the area under the Receiver Operating Characteristic curve (AROC), the sensitivity, the specificity, the positive and the negative predictive values, with corresponding 95% CIs.

The predictive efficacy of the risk score measured by AUC value was 0.85 (95% CI: 0.82 to 0.87), indicating a high level of accuracy of the model in discriminating between violent and non-violent women, with a sensitivity of 77.4% and specificity 75.7% at a cut-off -3 of the estimated risk score.

C-statistic values were calculated to assess performance of logistic regression models in discriminating mortality.

We compared the performance of our models in discriminating between invasive cancer and DCIS using AUC values.

Testing for a significant difference between the Model 1 AUR and Model 2 AUR shows that Model 2 performs significantly better than Model 1 in discriminating between persons requiring access to priority general treatment (P < 0.001; χ) see Figure  2.

As is indicated in Table  1, the PLS-DA model helps in discriminating all of the samples from the test set correctly.

If the hit priority of the TM5 feature was changed to be essential, the test model succeeded in discriminating two more inactives ((S -7-OH-DPAT and (S -7-OH-DPATand the full agoniS -7-OH-DPAT(becauS -7-OH-DPATthe phenolic hydroxy groups).

Sensitivity analysis (SA) is generally recognized as a worthwhile step to diagnose and remedy difficulties in identifying model parameters, and indeed in discriminating between model structures.

A significant IDI indicates that the new model performs better in discriminating cases and non-cases.