Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance in medical science. When a test is based on an observed variable that lies on a continuous scale, an assessment of the overall value of the test can be made through the use of a Receiver Operating Characteristic (ROC) curve. The ROC curve descibes the discrimination ability of a diagnosis test f...

A Receiver Operating Characteristic (ROC) curve reflects the performance of a system which decides between two competing actions in a test of statistical hypothesis. This paper addresses the inference on ROC curves for the following problem: how can one statistically validate the performance of a system with a claimed ROC curve, ROC0 say? Our proposed solution consists of two main components: F...

The receiver operating characteristic (ROC) curve is an important tool to gauge the performance of classifiers. In certain situations of high-throughput data analysis, the data is heavily class-skewed, i.e. most features tested belong to the true negative class. In such cases, only a small portion of the ROC curve is relevant in practical terms, rendering the ROC curve and its area under the cu...

This paper addresses an effective learning method that enables us to directly optimize neural network classifier's discrimination performance at a desired local operating range by maximizing a partial area under a receiver operating characteristic (ROC) or domain-specific curve, which is difficult to achieve with classification accuracy or mean squared error (MSE)-based learning methods. The ef...

Receiver operating characteristic (ROC) curve is widely applied in measuring discriminatory ability of diagnostic or prognostic tests. This makes ROC analysis one of the most active research areas in medical statistics. Many parametric and semiparametric estimation methods have been proposed for estimating the ROC curve and its functionals. In this paper, we propose a fully nonparametric Bayesi...

The area under an ROC curve (AUC) has been advocated as an evaluation criterion for bipartite ranking problems. In this paper, we study large deviation properties of the AUC; in particular, we derive a distribution-free large deviation bound for the AUC which serves to bound the expected accuracy of a ranking function in terms of its empirical AUC on an independent test sequence.1 A comparison ...

The aims of the present study were to evaluate the predictive value of the platelet-to-lymphocyte ratio for peritoneal metastasis in patients with gastric cancer and to construct an available preoperative prediction system for peritoneal metastasis. A total of 1080 patients with gastric cancer were enrolled in our study. The preoperative platelet-to-lymphocyte ratio and other serum markers and ...