Results 41 to 50 of about 133,681 (240)
Sparse Regression with Multi-type Regularized Feature Modeling
, 2020 Within the statistical and machine learning literature, regularization techniques are often used to construct sparse (predictive) models. Most regularization strategies only work for data where all predictors are treated identically, such as Lasso ...
Antonio, Katrien +3 more
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Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
GLM permutation - nonparametric inference for arbitrary general linear models [PDF]
, 2008 Introduction: Permutation methods are finding growing use in neuroimag- ing data analyses (e.g. randomise in FSL, SnPM in SPM, XBAMM/BAMM/CAMBA, etc).
Nichols, T. +3 more
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Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
BMC Genetics, 2017 Background Poor grain plumpness (GP) is one of the main constraints to reaching the yield potential of hybrid rice. Results In this study, the GP of 177 rice varieties was investigated in three locations across 2 years.
Erbao Liu +8 more
doaj +1 more source
An Interpretable Two-Phase Modeling Approach for Lung Cancer Survivability Prediction
Sensors, 2022 Although lung cancer survival status and survival length predictions have primarily been studied individually, a scheme that leverages both fields in an interpretable way for physicians remains elusive. We propose a two-phase data analytic framework that
Zahra Sedighi-Maman, Jonathan J. Heath
doaj +1 more source
POM‐Based Water Splitting Catalyst Under Acid Conditions Driven by Its Assembly on Carbon Nanotubes
Advanced Materials, EarlyView.A newly‐engineered POM‐based electrocatalyst incorporating non‐innocent counter cations exhibits fast kinetics for either the OER or HER under strongly acidic conditions (1 m H2SO4), depending on whether it is assembled on carbon nanotubes (1@CNT) or physically mixed with them (1/CNT). In water‐splitting tests using a two‐electrode setup, these systems
Eugenia P. Quirós‐Díez +8 more
wiley +1 more source
Robust statistical methods and the credibility movement of psychological science [PDF]
PeerJThe general linear model (GLM) is the most frequently applied family of statistical models in psychology. Within the GLM, the effects under study are estimated using the ordinary least squares (OLS) estimation.
Martina Sladekova, Andy P. Field
doaj +2 more sources
Neuroscience Informatics, 2021 Objective: The purpose of this study was to evaluate the gray matter (GM) alterations in patients with mesial temporal lobe epilepsy (MTLE) based on statistical models.
Zhensheng Li +6 more
doaj +1 more source
Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG [PDF]
, 2010 Background: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. Methods: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation
Cannadathu, S. +9 more
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