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The area under the effect curve (AUEC) is an integral of the effect of a drug over time, estimated as a previously-established function of concentration. It was proposed to be used instead of AUC in animal-to-human dose translation, as computer simulation shows that it could cope better with half-life and dosing schedule variations than AUC.
The main criticism to the ROC curve described in these studies regards the incorporation of areas with low sensitivity and low specificity (both lower than 0.5) for the calculation of the total area under the curve (AUC)., [19] as described in the plot on the right.
The absolute bioavailability is the dose-corrected area under curve (AUC) non-intravenous divided by AUC intravenous. The formula for calculating the absolute bioavailability, F, of a drug administered orally (po) is given below (where D is dose administered).
Total drug exposure is most often estimated by area under the curve (AUC) methods, with the trapezoidal rule (numerical integration) the most common method. Due to the dependence on the length of x in the trapezoidal rule, the area estimation is highly dependent on the blood/plasma sampling schedule. That is, the closer time points are, the ...
The AUC (area under the curve) of the ROC curve reflects the overall accuracy and the separation performance of the biomarker (or biomarkers), [3] and can be readily used to compare different biomarker combinations or models. [4] As a rule of thumb, the fewer the biomarkers that one uses to maximize the AUC of the ROC curve, the better.
It is common to report the area under the curve (AUC) to summarize a TOC or ROC curve. However, condensing diagnostic ability into a single number fails to appreciate the shape of the curve. The following three TOC curves are TOC curves that have an AUC of 0.75 but have different shapes. [citation needed]
The Partial Area Under the ROC Curve (pAUC) is a metric for the performance of binary classifier. It is computed based on the receiver operating characteristic (ROC) curve that illustrates the diagnostic ability of a given binary classifier system as its discrimination threshold is varied.
Area under the curve (receiver operating characteristic), a performance measure for binary classifiers Area under the curve (pharmacokinetics) , regarding plasma drug concentration-time curves Authentication Center in a GSM mobile phone network