For many years now, there is a growing interest around ROC curve for characterizing machine learning performances. This is particularly due to the fact that in real-world problems misclassification costs are not known and thus, ROC curve and related metrics such as the Area Under ROC curve (AUC) can be a more meaningful performance measures. In this paper, we propose a quadratic programming bas...

BACKGROUND Cyclosporine (CsA), Mycophenolate mofetil (MMF) and prednisolone (PSL) are widely used for the prevention of acute rejection after heart transplantation. Recently, the serum concentration - time curves (AUC) of CsA and MMF have been demonstrated to be precise predictors of acute rejection. METHODS AND RESULTS Fourteen heart transplant patients were treated concomitantly with CsA, M...

The optimisation of the Area Under the ROC Curve (AUC) has recently been proposed for learning ranking functions. However, the estimation of the AUC of a function on the true distribution of the examples based on its empirical value is still an open problem. In this paper, we present a data-dependent generalisation error bound for the AUC. This bound presents the advantage to be tight, but it a...

The area under the ROC (Receiver Operating Characteristic) curve, or simply AUC, has been widely used to measure model performance for binary classification tasks. It can be estimated under parametric, semiparametric and nonparametric assumptions. The non-parametric estimate of the AUC, which is calculated from the ranks of predicted scores of instances, does not always sufficiently take advant...

Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel meth...

To address the debate on the safety of generic substitution quantitatively, the author compared the change in AUC in virtual patients who were simulated for several different scenarios of generic substitution. In four scenarios of original (branded) to generic and generic to generic substitution, 5,000 virtual patients were simulated per scenario using the programming software R. The mean popul...

OBJECTIVE The aim of the present study was to investigate the usefulness of the CA-125 area under the curve (AUC) as a new kinetic parameter for predicting overall survival in patients with ovarian cancer. In addition, the relationship of CA-125 AUC with other prognostic factors of ovarian cancer was evaluated. METHODS Ninety-two patients that underwent primary line chemotherapy within 4 mont...