Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

The area under the ROC curve (AUC) is a natural performance measure when the goal is to find a discriminative decision function. We present a rigorous derivation of an AUC maximizing Support Vector Machine; its optimization criterion is composed of a convex bound on the AUC and a margin term. The number of constraints in the optimization problem grows quadratically in the number of examples. We...

AUC is an important parameter in pharmacokinetic studies. There are different ways to calculate AUC. Sometime, the statistician or pharmacokineticist has to choose one particular method to calculate AUC depending on the actual concentration data. Among many pharmacokinetic approaches and modeling analyses, traditional trapezoidal, log-linear trapezoidal, Lagrange polynomial integration, and Pur...

Developing novel nuclear cardiology approaches requires evaluating their diagnostic ability. Statistical measures such as sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under the curve (AUC) are useful to evaluate the diagnostic value of novel imaging parameters. This paper reviews key statistical methods used in the evaluation of diagnostic tests and highligh...

In analyzing data from a survey, researchers often need to compare the effectiveness of several logistic regression models. The receiver operating characteristic curve offers one way to measure effectiveness of prediction, by calculating the area under the curve (AUC). We present a SAS macro for calculating AUC that takes the survey weights into account. For comparing logistic regression models...

The summary receiver operating characteristic (SROC) curve has been recommended to represent the performance of a diagnostic test, based on data from a meta-analysis. However, little is known about the basic properties of the SROC curve or its estimate. In this paper, the position of the SROC curve is characterized in terms of the overall diagnostic odds ratio and the magnitude of inter-study h...

Support vector machine (SVM) is biased towards the majority class, in some case dataset is class-imbalanced and the bias is even larger for high-dimensional. In order to improve the classification accuracy of SVM on high-dimensional imbalanced data, we combine signal-noise ratio (SNR) and under-sampling technique based on K-means. In this article firstly we apply SNR into feature selection to r...

the main purpose of this study is landslide hazard assessment the ziarat watershed (golestan province) using information value and lnrf models within geographic information. at first stage, a landslide inventory map was prepared in the study area using earlier reports and aerial photographs, and a total of 50 landslides was mapped and out of which 35 (70%) were randomly selected for building la...