Results 61 to 70 of about 63,287 (274)

Shared Genetic Effects and Antagonistic Pleiotropy Between Multiple Sclerosis and Common Cancers

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epidemiologic studies have reported inconsistent altered cancer risk in individuals with multiple sclerosis (MS). Factors such as immune dysregulation, comorbidities, and disease‐modifying therapies may contribute to this variability.
Asli Buyukkurt, Marius Ygonia, Ali Manouchehrinia, Philippe Lefrançois, Ingrid Kockum, Adil Harroud   +5 more
wiley   +1 more source

Obesity Subtypes and Longitudinal Trajectories of Function Over Seven Years of Follow‐Up: Data From the Multicenter Osteoarthritis Study

Arthritis Care &Research, EarlyView.
Objective Obesity, defined by body mass index (BMI) ≥30 kg/m2, is a risk factor for functional limitations in people with knee osteoarthritis (OA). However, function varies among such individuals. Our objective was to evaluate the implications of obesity subtypes on longitudinal patterns of physical functioning in people with or at risk for knee OA ...
Kristine Godziuk, Sarah Tilley, Michael LaValley, Michael C. Nevitt, Cora E. Lewis, James C. Torner, Tuhina Neogi, for the Multicenter Osteoarthritis Study Group   +7 more
wiley   +1 more source

Variational Bayesian Quantile Regression with Non-Ignorable Missing Response Data

Axioms
For non-ignorable missing response variables, the mechanism of whether the response variable is missing can be modeled through logistic regression. In Bayesian computation, the lack of a conjugate prior for the logistic function poses a significant ...
Juanjuan Zhang, Weixian Wang, Maozai Tian   +2 more
doaj   +1 more source

Clinical, histological, and serological predictors of renal function loss in lupus nephritis.

Arthritis Care &Research, Accepted Article.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang, Laurence Magder, Daniel Goldman, Judith A. James, Joel M Guthridge, Carla Guthridge, Peter Izmirly, Jill P Buyon, H.Michael Belmont, Richard A. Furie, Noa Schwartz, Chaim Putterman, Jennifer L. Barnas, Jennifer H. Anolik, Sarah French, Maria Dall'era, Avi Z. Rosenberg, Jeffrey Hodgin, Dawit S. Demeke, the Accelerating Medicines Partnership RA/SLE Network, Michelle Petri, Andrea Fava   +21 more
wiley   +1 more source

Variational Bayesian Variable Selection for High-Dimensional Hidden Markov Models

Mathematics
The Hidden Markov Model (HMM) is a crucial probabilistic modeling technique for sequence data processing and statistical learning that has been extensively utilized in various engineering applications.
Yao Zhai, Wei Liu, Yunzhi Jin, Yanqing Zhang   +3 more
doaj   +1 more source

A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network

Micromachines, 2023
Memristor crossbar arrays are a promising platform for neuromorphic computing. In practical scenarios, the synapse weights represented by the memristors for the underlying system are subject to process variations, in which the programmed weight when read
Di Gao, Xiaoru Xie, Dongxu Wei
doaj   +1 more source

Variational Bayesian Last Layers

CoRR
We introduce a deterministic variational formulation for training Bayesian last layer neural networks. This yields a sampling-free, single-pass model and loss that effectively improves uncertainty estimation. Our variational Bayesian last layer (VBLL) can be trained and evaluated with only quadratic complexity in last layer width, and is thus (nearly ...
James Harrison, John Willes, Jasper Snoek   +2 more
openaire   +3 more sources

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
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, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Variational Bayesian Pseudo-Coreset

CoRR
The success of deep learning requires large datasets and extensive training, which can create significant computational challenges. To address these challenges, pseudo-coresets, small learnable datasets that mimic the entire data, have been proposed. Bayesian Neural Networks, which offer predictive uncertainty and probabilistic interpretation for deep ...
Hyungi Lee, Seungyoo Lee, Juho Lee 0001
openaire   +3 more sources

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
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, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source