Results 31 to 40 of about 688,609 (284)
Semi-Parametric Joint Modeling of Survival and Longitudinal Data: The R Package JSM
Journal of Statistical Software, 2020 This paper is devoted to the R package JSM which performs joint statistical modeling of survival and longitudinal data. In biomedical studies it has been increasingly common to collect both baseline and longitudinal covariates along with a possibly ...
Cong Xu +2 more
doaj +1 more source
Unsupervised cryo-EM data clustering through adaptively constrained K-means algorithm
, 2016 In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules.
Mao, Youdong +3 more
core +7 more sources
A Constrained EM Algorithm for Independent Component Analysis [PDF]
, 2001 We introduce a novel way of performing independent component analysis using a constrained version of the expectation-maximization (EM) algorithm. The source distributions are modeled as D one-dimensional mixtures of gaussians.
Weber, Markus, Welling, Max
core +2 more sources
EB lifetime distributions as alternative to the EP lifetime distributions
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2014 In this paper we consider lifetime distributions called EB-Max distribution and EB-Min. In the conditions of the Poisson’s Limit Theorem it is shown that EB-Max distribution may be approximated by its analogous called EP-Max lifetime distribution and EB ...
Lupu Carmen Elena +2 more
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Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification
, 2018 The cryo-electron microscope (cryo-EM) is increasingly popular these years. It helps to uncover the biological structures and functions of macromolecules. In this paper, we address image denoising problem in cryo-EM. Denoising the cryo-EM images can help
Cai, Jian-Feng +6 more
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Comparison of the Average Kappa Coefficients of Two Binary Diagnostic Tests with Missing Data
Mathematics, 2021 The average kappa coefficient of a binary diagnostic test is a parameter that measures the average beyond-chance agreement between the diagnostic test and the gold standard.
José Antonio Roldán-Nofuentes +1 more
doaj +1 more source
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
, 2011 We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. definite clause programs containing probabilistic facts with a parameterized distribution.
Kameya, Y., Sato, T.
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FEBS Open Bio, EarlyView.In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source
A Monomial-Oriented GVW for Computing Gr\"obner Bases [PDF]
, 2014 The GVW algorithm, presented by Gao et al., is a signature-based algorithm for computing Gr\"obner bases. In this paper, a variant of GVW is presented. This new algorithm is called a monomial-oriented GVW algorithm or mo-GVW algorithm for short.
Huang, Zhenyu +3 more
core
Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz +11 more
wiley +1 more source