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The area under the ROC curve indicated good ability of the model to predict mortality (area = 85%, 95% CI 83 87).
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However, its personal separation index was high, indicating good ability of the modified scale to differentiate between groups of patients with various degrees for muscle weakness.
The caregivers' results indicated good work ability (WAI 37.4 ± 5.1), health related quality of life was superior to the German sample (SF-12 physical CSS 49.2 ± 8.0; mental CSS 54.1 ± 6.6).
The AUC was 0.927 955% CI: 0.885 to 0.957), indicating good discriminant ability.
Predictive R2 for the test set was 0.77, indicating good predictive ability of the model.
A low probability of error of individual features as obtained using baysian classifier would indicate good discriminatory ability and asserts the usefulness of the feature.
Good correlation between experimentally obtained data and ones predicted by using QSRR-ANN on previously unseen data sets indicates good predictive ability of the model.
Low scores indicate good functional ability.
An AROC value ≥0.70 indicates good discrimination ability.
The area under the curve was 0.83 (95% confidence interval (CI) = 0.74 – 0.93) indicating good discriminatory ability.
Overall, the value of the area under the curve (AUC) was 0.79 (95% CI, 0.75-0.83), indicatingoododiscriminationon ability.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com