CONTEXT Chronic hepatitis C virus (HCV) infection outcomes include liver failure, hepatocellular carcinoma (HCC), and liver-related death. OBJECTIVE To assess the association between sustained virological response (SVR) and all-cause mortality in patients with chronic HCV infection and advanced hepatic fibrosis. DESIGN, SETTING, AND PATIENTS An international, multicenter, long-term follow-u...

BACKGROUND AND AIMS The risk of hepatocellular cancer (HCC) after sustained virological response (SVR) with direct-acting antivirals (DAA) is unclear. Our aim was to examine the risk and determinants of HCC in patients cured with DAA. METHODS We conducted a retrospective cohort study of hepatitis C virus patients who were treated with DAA in any of the 129 Veterans Health Administration hospi...

BACKGROUND Single nucleotide polymorphism in the interleukin28B (IL28B) gene was recently shown to be associated with a significant increase in response to interferon-α and ribavirin treatment in patients with chronic hepatitis C. Similarly, thyroid disease (TD) occurring during treatment confer an improved sustained virologic response (SVR). OBJECTIVES To determine the role of IL28B genotype...

Loadability limits are critical points of particular interest in voltage stability assessment, indicating how much a system can be stressed from a given state before reaching instability. Thus estimating the loadability margin of a power system is essential in the real time voltage stability assessment. A new methodology is developed based on Support Vector Regression (SVR) which is the most co...

Support vector regression (SVR) and support vector classification (SVC) are popular learning techniques, but their use with kernels is often time consuming. Recently, linear SVC without kernels has been shown to give competitive accuracy for some applications, but enjoys much faster training/testing. However, few studies have focused on linear SVR. In this paper, we extend state-of-the-art trai...

In this article, we propose a novel application for Support Vector Regression (SVR) for strategies of executing orders on stock exchanges. We use SVR for predicting volume participation function in execution strategies which try to achieve Volume Weighted Average Price (VWAP) measure of quality of the execution. Moreover, we use SVR with a priori knowledge about stock prices in order to further...

The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature s...

Linear regression (LR) and support vector regression (SVR) are widely used in data analysis. Geometrical correlation learning (GcLearn) was proposed recently to improve the predictive ability of LR and SVR through mining and using correlations between data of a variable (inner correlation). This paper theoretically analyzes prediction performance of the GcLearn method and proves that GcLearn LR...

OBJECTIVES Identifying the predictive factors of Sustained Virological Response (SVR) represents an important challenge in new interferon-based DAA therapies. Here, we analyzed the kinetics of antiviral response associated with a triple drug regimen, and the association between negative residual viral load at different time points during treatment. METHODS Twenty-three HCV genotype 1 (GT 1a n...