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Exact(6)
Desjardins, et al [10] created a novel forward-solutions-based inverse method for simultaneous and accurate characterization of permeability and conductivity by computing the areas under scaled PEC signals.
The two curves were compared by computing the areas under the ROC curves [ 12, 13].
The four curves were compared by computing the areas under the curves.
A comparison of the six curves was done by computing the areas under the ROC curves.
Discrimination was tested by 2 × 2 classification matrices and by computing the areas under the receiver operating characteristic curves.
Mean health state durations were estimated from censored survival data (product limit method) up to 72 months from randomisation by computing the areas between the survival curve estimates for the transition times.
Similar(54)
Classification performance was assessed by computing the area under the curve (AUC).
COP area was calculated by computing the area of an ellipse enclosing 95% of the COP signal.
The temporal dynamics of the XTT assay was summarized by computing the area under the curve (trapezoidal method).
Discrimination was determined by computing the area under the receiver-operating characteristic curve (AUC, represented as area ± SE).
Models were compared by computing the area under the curve (AUC) of the ROC using the trapezoidal method.
More suggestions(17)
by integrating the areas
by superimposing the areas
by adding the areas
by inputting the areas
by equating the areas
by removing the areas
by exploring the areas
by identifying the areas
by computing the averages
by averaging the areas
by measuring the areas
by comparing the areas
by examining the areas
by exposing the areas
by tracing the areas
by computing the eigenvalues
by narrowing the areas
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com