Search results for " Selection"

Available evidence on re-irradiation with stereotactic ablative radiotherapy following high-dose previous thoracic radiotherapy for lung malignancies

2015

Patients affected with intra-thoracic recurrences of primary or secondary lung malignancies after a first course of definitive radiotherapy have limited therapeutic options, and they are often treated with a palliative intent. Re-irradiation with stereotactic ablative radiotherapy (SABR) represents an appealing approach, due to the optimized dose distribution that allows for high-dose delivery with better sparing of organs at risk. This strategy has the goal of long-term control and even cure. Aim of this review is to report and discuss published data on re-irradiation with SABR in terms of efficacy and toxicity. Results indicate that thoracic re-irradiation may offer satisfactory disease c…

Introduction to coronary imaging with 64-slice computed tomography

2005

The aim of this article is to illustrate the main technical improvements in the last generation of 64-row CT scanners and the possible applications in coronary angiography. In particular, we describe the new physical components (X-ray tube-detectors system) and the general scan and reconstruction parameters. We then define the scan protocols for coronary angiography with the new generation of 64-row CT scanners to enable radiologists to perform a CT study on the basis of the diagnostic possibilities.

Natural selection constrains personality and brain gene expression differences in Atlantic salmon (Salmo salar).

2015

ABSTRACT In stream-spawning salmonid fishes there is a considerable variation in the timing of when fry leave the spawning nests and establish a feeding territory. The timing of emergence from spawning nests appears to be related to behavioural and physiological traits, e.g. early emerging fish are bolder and more aggressive. In the present study, emerging Atlantic salmon (Salmo salar L.) alevins were sorted into three fractions: early, intermediate and late emerging. At the parr stage, behaviour, stress responses, hindbrain monoaminergic activity and forebrain gene expression were explored in fish from the early and late emerging fractions (first and last 25%). The results show that when s…

Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates

2022

Abstract Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This study aimed to provide a new approach with better performance for landslide mapping and adopting readily available variables. In addition, it investigates the capability of a state-of-the-art model developed using the group method of data handling (GMDH) to spatially model LS. Furthermore, hybridized models of GMDH were developed using different metaheuristic algorithms. The study area was the Bonghwa region of South Korea, for which an accurate landslide inventory dataset is available. We considered a total of 13 spatial covariates (altitude, slope, aspect, topographic wetness index, val…

Is tourism firm competitiveness driven by different internal or external specific factors?: New empirical evidence from Spain

2015

Abstract The quest to understand the multilevel antecedents of competitiveness has led to a separation of approaches. On one side of the question are the environment theories that analyze the structural characteristics of the general and competitive environment. On the other side are the Resource Based View and its extensions that highlight firm-specific resources and capabilities as the main basis of firms' competitiveness. However, in recent years the nature of competition and shifting economic conditions have given rise to new theoretical approaches that complement the assumptions underlying both environmental and firm theories. Specifically, this study contributes by examining the regio…

Feature Selection for Ensembles of Simple Bayesian Classifiers

2002

A popular method for creating an accurate classifier from a set of training data is to train several classifiers, and then to combine their predictions. The ensembles of simple Bayesian classifiers have traditionally not been a focus of research. However, the simple Bayesian classifier has much broader applicability than previously thought. Besides its high classification accuracy, it also has advantages in terms of simplicity, learning speed, classification speed, storage space, and incrementality. One way to generate an ensemble of simple Bayesian classifiers is to use different feature subsets as in the random subspace method. In this paper we present a technique for building ensembles o…

Ensemble Feature Selection Based on the Contextual Merit

2001

Recent research has proved the benefits of using ensembles of classifiers for classification problems. Ensembles constructed by machine learning methods manipulating the training set are used to create diverse sets of accurate classifiers. Different feature selection techniques based on applying different heuristics for generating base classifiers can be adjusted to specific domain characteristics. In this paper we consider and experiment with the contextual feature merit measure as a feature selection heuristic. We use the diversity of an ensemble as evaluation function in our new algorithm with a refinement cycle. We have evaluated our algorithm on seven data sets from UCI. The experiment…

2004

This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to …

Ensemble Feature Selection Based on Contextual Merit and Correlation Heuristics

2001

Recent research has proven the benefits of using ensembles of classifiers for classification problems. Ensembles of diverse and accurate base classifiers are constructed by machine learning methods manipulating the training sets. One way to manipulate the training set is to use feature selection heuristics generating the base classifiers. In this paper we examine two of them: correlation-based and contextual merit -based heuristics. Both rely on quite similar assumptions concerning heterogeneous classification problems. Experiments are considered on several data sets from UCI Repository. We construct fixed number of base classifiers over selected feature subsets and refine the ensemble iter…

Signals of major histocompatibility complex overdominance in a wild salmonid population

2009

The major histocompatibility complex (MHC) contains the most variable genes in vertebrates, but despite extensive research, the mechanisms maintaining this polymorphism are still unresolved. One hypothesis is that MHC polymorphism is a result of balancing selection operating by overdominance, but convincing evidence for overdominant selection in natural populations has been lacking. We present strong evidence consistent with MHC-specific overdominance in a free-living population of Arctic charr (Salvelinus alpinus) in northernmost Europe. In this population, where just two MHC alleles were observed, MHC heterozygous fish had a lower parasite load, were in better condition (as estimated by a…