AIMC Topic: Linear Models

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Markers of endothelial damage and coagulation impairment in patients with severe sepsis resuscitated with hydroxyethyl starch 130/0.42 vs Ringer acetate.

Journal of critical care Dec 8, 2015
PURPOSE: The Scandinavian Starch for Severe Sepsis/Septic Shock (6S) trial showed increased mortality in patients resuscitated with hydroxyethyl starch 130/0.42 (HES) vs Ringer acetate. Different effects of the fluids on the endothelium may have cont...
Middle Aged Plasminogen Activator Inhibitor 1 Sepsis Linear Models Plasma Substitutes Logistic Models Aged Treatment Outcome Humans Resuscitation Adult Thrombomodulin Blood Coagulation Biomarkers Male Female Odds Ratio Isotonic Solutions Hydroxyethyl Starch Derivatives
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Robotic pilot study for analysing spasticity: clinical data versus healthy controls.

Journal of neuroengineering and rehabilitation Dec 2, 2015
BACKGROUND: Spasticity is a motor disorder that causes significant disability and impairs function. There are no definitive parameters that assess spasticity and there is no universally accepted definition. Spasticity evaluation is important in deter...
Female Adult Cross-Sectional Studies Male Humans Algorithms Brain Injuries Robotics Linear Models Muscle Spasticity Middle Aged Pilot Projects Models, Theoretical
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The feature selection bias problem in relation to high-dimensional gene data.

Artificial intelligence in medicine Nov 14, 2015
OBJECTIVE: Feature selection is a technique widely used in data mining. The aim is to select the best subset of features relevant to the problem being considered. In this paper, we consider feature selection for the classification of gene datasets. G...
Humans Algorithms Decision Support Techniques Computational Biology Gene Expression Regulation, Neoplastic Support Vector Machine Databases, Genetic Reproducibility of Results Biomarkers, Tumor Gene Expression Profiling Pattern Recognition, Automated Oligonucleotide Array Sequence Analysis Bias Data Mining Linear Models
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SIM-ELM: Connecting the ELM model with similarity-function learning.

Neural networks : the official journal of the International Neural Network Society Nov 4, 2015
This paper moves from the affinities between two well-known learning schemes that apply randomization in the training process, namely, Extreme Learning Machines (ELMs) and the learning framework using similarity functions. These paradigms share a com...
Random Allocation Machine Learning Algorithms Humans Databases, Factual Heart Diseases Neural Networks, Computer Linear Models Reproducibility of Results Image Processing, Computer-Assisted
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A non-penalty recurrent neural network for solving a class of constrained optimization problems.

Neural networks : the official journal of the International Neural Network Society Oct 27, 2015
In this paper, we explain a methodology to analyze convergence of some differential inclusion-based neural networks for solving nonsmooth optimization problems. For a general differential inclusion, we show that if its right hand-side set valued map ...
Computer Simulation Markov Chains Linear Models Problem Solving Mathematics Neural Networks, Computer Algorithms
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A linear functional strategy for regularized ranking.

Neural networks : the official journal of the International Neural Network Society Oct 23, 2015
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularizati...
Linear Models Humans Neural Networks, Computer Risk Assessment Machine Learning Least-Squares Analysis Algorithms Hypoglycemia
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Finite-time synchronization of fractional-order memristor-based neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society Oct 19, 2015
In this paper, we consider the problem of finite-time synchronization of a class of fractional-order memristor-based neural networks (FMNNs) with time delays and investigated it potentially. By using Laplace transform, the generalized Gronwall's ineq...
Neural Networks, Computer Algorithms Feedback Linear Models
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Spatially regularized machine learning for task and resting-state fMRI.

Journal of neuroscience methods Oct 16, 2015
BACKGROUND: Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades.
Humans Brain Mental Processes Linear Models Rest Fingers Magnetic Resonance Imaging Motor Activity Computer Simulation Brain Mapping Models, Neurological Visual Perception Neural Pathways Reproducibility of Results Datasets as Topic Neuropsychological Tests Support Vector Machine
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Development of sediment load estimation models by using artificial neural networking techniques.

Environmental monitoring and assessment Oct 13, 2015
This study aims at the development of an artificial neural network-based model for the estimation of weekly sediment load at a catchment located in northern part of Pakistan. The adopted methodology has been based upon antecedent sediment conditions,...
Pakistan Linear Models Geologic Sediments Models, Theoretical Environmental Monitoring Environmental Pollutants Neural Networks, Computer Algorithms
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Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

Journal of chromatography. A Oct 1, 2015
The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column....
Chromatography, Gas Nonlinear Dynamics Linear Models Hydrocarbons Databases, Factual Adamantane Humans Neural Networks, Computer
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