Results 81 to 90 of about 12,151,236 (300)
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in patients with giant cell arteritis (GCA). Methods This multicenter retrospective study included patients with GCA who received secukinumab at 14 Italian centers with at least six months of follow‐up.
Luca Iorio +28 more
wiley +1 more source
Simulation Study of Autocorrelated Error Using Bayesian Quantile Regression
The purpose of this study is to compare the ability of the Classical Quantile Regression method and the Bayesian Quantile Regression method in estimating models that contain autocorrelated error problems using simulation studies.
Nayla Desviona, Ferra Yanuar
doaj +1 more source
Objectives This study aimed to determine whether gout flare resolution is associated with physical activity and sleep. These findings were intended to inform the future development of a definition for flare resolution. Methods Data from 81 participants with gout who experienced >1 flare during a 6‐month prospective observational study were included ...
Sarah Stewart +12 more
wiley +1 more source
Hierarchic Bayesian models for kernel learning [PDF]
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance when compared to that obtained from any single data source.
Rogers, S. +3 more
core +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
The Generalized Method of Moments in the Bayesian Framework and a Model of Moment Selection Criterion [PDF]
While the classical framework has a rich set of limited information procedures such as GMM and other related methods, the situation is not so in the Bayesian framework.
Jae-Young Kim
core
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
APPLYING BAYESIAN METHODS FOR METROLOGICAL EVALUATION AND INTERPRETATION OF FORENSIC EVIDENCE
The paper summarizes Bayesian approaches to uncertainty assessment of forensicexamination results and o#ers a brief overview of current achievements in the applicationof the likelihood ratio concept in forensic practice.
G. Bebeshko +3 more
doaj
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Contribution to the phylogeny of Microgastrinae (Hymenoptera: Braconidae) based on mitochondrial COI and nuclear 28S rDNA genes, with comments on the identity of Pholetesor circumscriptus (Nees, 1834) [PDF]
Microgastrines are diverse group of endoparasitoid wasps attacking caterpillars (Lepidoptera). Despite their importance in biological control, there is still no consensus concerning the phylogeny relationships among taxa.
Parisa Abdoli +4 more
doaj

