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We calculated parsimonious values for select variables associated with in-patient hospitalization and compared sensitivity and specificity of these models to ordinal staging of renal disease.
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For this dataset the SVM models have a similar accuracy to the RF models; the balance between sensitivity and specificity of the models differs, however.
The sensitivity and specificity of the models for each disease are shown in ROC curves (Figure 3A C).
The sensitivity and specificity of the models were calculated.
To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed.
A receiver operating characteristic curve was calculated to assess sensitivity and specificity of the models.
To evaluate the sensibility and specificity of the models, receiver operating characteristic (ROC) curves were constructed by choosing cutpoints and computing the sensitivity against specificity.
The specificity of the models ranges from 28.4%to38.8%8%, with corresponding investigation rates (computed tomography, lumbar puncture, or both) from 63.7% to 73.5%.
These cut points illustrate the tradeoff in sensitivity and specificity of the model over the range of predicted values.
The corresponding sensitivity and specificity of the model were 65.57% and 44.74%, respectively.
The specificity of the model was 94.2%, whereas the sensitivity was 20.4%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com