Desirable features of support vector regression (SVR) models have led to researchers extending them to survival problems. In current paper we evaluate and compare performance of different SVR models and the Cox model using simulated and real data sets with different characteristics. Several SVR models are applied: 1) SVR with only regression constraints (standard SVR); 2) SVR with regression an...

We propose a novel idea of regression – balancing the distances from a regression function to all examples. We created a method, called balanced support vector regression (balanced SVR) in which we incorporated this idea to support vector regression (SVR) by adding an equality constraint to the SVR optimization problem. We implemented our method for two versions of SVR: ε-insensitive support ve...

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...

BACKGROUND Syncope is a sudden transient loss of consciousness and postural tone caused by cerebral hypoperfusion. The most common form is vasovagal syncope (VVS). Presyncopal progressive early hypotension in older VVS patients is caused by reduced cardiac output (CO); younger patients have reduced systemic vascular resistance (SVR). Using a priori criteria for reduced CO (↓CO) and SVR (↓SVR), ...

BACKGROUND Achievement of a sustained virologic response (SVR) after treatment for Hepatitis C infection is associated with improved outcomes. This meta-analysis aimed to determine the impact of SVR on long-term mortality risk compared with nonresponders in a range of populations. METHODS An electronic search identified all studies assessing all-cause mortality in SVR and non-SVR patients. El...

Background and purpose: Machine learning is a class of modern and strong tools that can solve many important problems that nowadays humans may be faced with. Support vector regression (SVR) is a way to build a regression model which is an incredible member of the machine learning family. SVR has been proven to be an effective tool in real-value function estimation. As a supervised-learning appr...

BACKGROUND Achievement of sustained virologic response (SVR) and factors associated with treatment failure in hepatitis C virus (HCV) genotype 3 have been described in tertiary and referral care settings, with rates of SVR reported to range between 72% and 89%. Fewer data exist on SVR outside of these settings. OBJECTIVE To describe rates of SVR and characterize factors associated with achiev...

The paper presents the application of support vector regression (SVR) to accurate forecasting of the tangential displacement of a concrete dam. The SVR nonlinear autoregressive model with exogenous inputs (NARX) was developed and tested using experimental data collected during fourteen years. A total of 573 data were used for training of the SVR model whereas the remaining 156 data were used to...

This paper explores the feasibility of applying support vector regression (SVR) kernel-based supervised learning method to develop hot mix asphalt (HMA) dynamic modulus (|E*|) predictive models. SVR-based prediction models were developed using the latest comprehensive |E*| database that is available to the researchers. The SVR model predictions were compared with the existing regression-based p...