Results 21 to 30 of about 46,519 (215)
Zero-Inflated Data Analysis Using Graph Neural Networks with Convolution
ComputersZero-inflated count data are characterized by an excessive frequency of zeros that cannot be adequately analyzed by a single distribution, such as Poisson or negative binomial.
Sunghae Jun
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Collaterals are crucial factors that influence the infarct growth rate (IGR). We aimed to determine whether a comprehensive multimodal collateral score (MCS), incorporating collateral assessment at the arterial, tissue, and venous levels, is associated with functional independence and provides incremental prognostic value over ...
Giorgio Busto +12 more
wiley +1 more source
AppliedMathThis study proposes a transformed two-part bootstrap confidence interval (TTB-CI) for zero-inflated count data. The method combines a standard zero-inflated mixture formulation, parametric bootstrap, and monotone transformations to improve inference for ...
Sangsung Park, Sunghae Jun
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Performance of the Ridge and Liu Estimators in the zero-inflated Bell Regression Model
Journal of Mathematics, 2022 The Poisson regression model is popularly used to model count data. However, the model suffers drawbacks when there is overdispersion—when the mean of the Poisson distribution is not the same as the variance.
Zakariya Yahya Algamal +3 more
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A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics
Genome Biology, 2020 Background Single-cell RNA sequencing is a powerful tool for characterizing cellular heterogeneity in gene expression. However, high variability and a large number of zero counts present challenges for analysis and interpretation.
Kwangbom Choi +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay +13 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To determine whether myelin‐sensitive quantitative MRI reveals microstructural abnormalities in normal‐appearing cortex (NACtx) in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), indicating that conventional MRI underestimates remission residual cortical injury.
Valentina Camera +20 more
wiley +1 more source
EM Estimation for Zero- and k-Inflated Poisson Regression Model
Computation, 2021 Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the
Monika Arora, N. Rao Chaganty
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch +5 more
wiley +1 more source