Results 81 to 90 of about 6,276,816 (299)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
The Generalized Exponential Distribution As a Lifetime Model under Different Loss Functions
Data Science Journal, 2009 Bayes estimates of the unknown parameter and the reliability function for the generalized exponential model are derived. Bayes estimates are obtained under various losses such as the squared error, the absolute error, the squared log error, and the ...
A Asgharzadeh, R Rezaei
doaj +1 more source
Efficacy of Inebilizumab in N‐MOmentum Trial Participants With or Without Prior Immunosuppressants
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT This post hoc analysis examined the impact of prior immunosuppressants on the long‐term efficacy and safety of inebilizumab, a cluster of differentiation 19+ B‐cell–depleting monoclonal antibody, in participants with aquaporin‐4–seropositive neuromyelitis optica spectrum disorder from the N‐MOmentum trial (NTC02200770).
Bruce A. C. Cree +9 more
wiley +1 more source
Reliability estimation of Weibull Lomax distribution via Bayesian approach [PDF]
Memoirs of the Scientific Sections of the Romanian Academy, 2023 Weibull Lomax distribution is considered. Bayesian method of estimation is employed in order to estimate the reliability function of Weibull Pareto distribution by using non-informative and beta priors.
Arun Kumar Rao, Himashu Pandey
doaj
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source
Investigation of scale parameter for the Weibull-Chen distribution
Research in StatisticsWithin this article, we estimate the scale parameter for the Weibull-Chen distribution and calculate posterior distributions. This analysis involves the application of the Bayesian technique, which utilizes two non-informative priors along with three ...
Mohamed Mubarak, Fathy H. Riad
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Building on our prior Behavioral Risk Factor Surveillance System analysis identifying adults aged 18–39 as the primary driver of the national increase in self‐reported cognitive disability, we examined factors associated with this rise using 2013–2024 U.S. BRFSS data. Methods We analyzed U.S.
Adam de Havenon +9 more
wiley +1 more source
Estimation of Rényi entropy of linear failure rate distribution based on Generalized Type- II Hybrid Censored Samples [PDF]
المجلة العلمية للدراسات والبحوث المالية والتجاريةEntropy is an essential term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we estimate the Rényi entropy measure of a linear failure rate distribution when data are generalized type-II hybrid ...
Dina Samir
doaj +1 more source
A Regularized Attribute Weighting Framework for Naive Bayes
IEEE Access, 2020 The Bayesian classification framework has been widely used in many fields, but the covariance matrix is usually difficult to estimate reliably. To alleviate the problem, many naive Bayes (NB) approaches with good performance have been developed. However,
Shihe Wang, Jianfeng Ren, Ruibin Bai
doaj +1 more source
Deleted Estimates of the Bayes Risk
The Annals of Statistics, 1973 Consider the usual decision theoretic situation where one observes a random vector $X$ from which an estimate of its classification $\theta \in \{0, 1\}$ is to be made. If one knows the a priori probabilities for $\theta$ and the conditional densities of $X$ given $\theta$ then the smallest probability of error which can be achieved is called the Bayes
openaire +3 more sources