OBJECTIVES The combination of pegylated interferon-α and ribavirin is a standard-of-care (SOC) treatment for chronic hepatitis C (CHC), and it achieves a sustained virological response (SVR) in 41-52% of genotype 1 and in 73-79% of genotype 3 patients. In a few clinical trials, the combination of fluvastatin and SOC increased the SVR in genotype 1 patients. METHODS This prospective study enro...

OBJECTIVE To identify apparent adverse effects of treatment of chronic hepatitis C and their relationship to sustained virologic response (SVR). METHODS A retrospective study was conducted of all Hepatitis C virus (HCV)-infected patients treated with pegylated interferon and ribavirin in an academic ambulatory infectious disease practice. Clinical and laboratory characteristics were compared ...

background despite significant advances in the treatment of chronic hepatitis c in the past decades, factors which can affect response rates to combination therapy; peginterferon and ribavirin, are still under study and reaching sustained virological response (svr) is affected by several different factors. objectives to investigate predictor factors contributing to svr in iranian patients. pati...

In this paper, robust fuzzy neural networks (FNNs) are proposed to identify chaotic systems. In the proposed FNNs, integrating support vector regression (SVR) and annealing robust time-varying learning algorithm (ARTVLA) is adopted to optimize the structure of neural networks. In the evolutionary procedure, first, SVR is adopted to determine the number of hidden layer nodes and the initial stru...

This paper presents dynamic available transfer capability (DATC) determination in power system restructuring environment using support vector regression (SVR). Dynamic available transfer capability is first determined based on the conventional method of potential energy boundary surface transient energy function. Simulations were carried out on a WSCC 3-machine 9-bus system and a Practical Sout...

Support Vector Regression (SVR) is a kernel based regression method capable of implementing a variety of regularisation techniques. Implementation of SVR usually follows a dual optimisation technique which includes Vapnik's -insensitive zone. The number of terms in the resulting SVR approximation function is dependent on the size of this zone, but improving sparsity by increasing the size of th...

The recent Sparse Voronoi Refinement (SVR) Algorithm for mesh generation has the fastest theoretical bounds for runtime and memory usage. We present a robust practical software implementation of the SVR for meshing a piecewise linear complex in 3 dimensions. Our software is competitive in runtime with state of the art freely available packages on generic inputs, and on pathological worse cases ...

In [1], with the evidence framework, the almost inversely linear dependency between the optimal parameter r in norm-r support vector regression machine r-SVR and the Gaussian input noise is theoretically derived. When r takes a non-integer value, r-SVR cannot be easily realized using the classical QP optimization method. This correspondence attempts to achieve two goals: (1) The Newton-decent-m...

The recent Sparse Voronoi Refinement (SVR) Algorithm for mesh generation has the fastest theoretical bounds for runtime and memory usage. We present a robust practical software implementation of the SVR for meshing a piecewise linear complex in 3 dimensions. Our software is competitive in runtime with state of the art freely available packages on generic inputs, and on pathological worse cases ...