Results 61 to 70 of about 914,252 (305)

Venous Thromboembolism in Pediatric Bone Sarcoma Patients: A 10‐Year, Single‐Institution Experience Encompassing the COVID‐19 Pandemic

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa, Shou Xu, Mark Zobeck, Sarah E. Sartain, Nino Rainusso, Lisa Wang, Nicole Montgomery, Paige Wheaton, Sarah Whittle   +8 more
wiley   +1 more source

Serological Benefit of SARS‐CoV‐2 Vaccination Relative to Infection in Children With Acute Lymphoblastic Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with acute lymphoblastic leukemia (ALL) are at risk of severe outcomes from SARS‐CoV‐2 (SCV2). In the post‐pandemic context, where most children have been infected with SCV2, there are limited data on whether vaccination remains beneficial in children with ALL.
Janna R. Shapiro, Freda Qi, Karen Colwill, Alina D. Dorogy, Ying Liu, Michelle Science, Anne‐Claude Gingras, James M. Rini, Sumit Gupta, Sarah Alexander, Shelly Bolotin, Tania H. Watts   +11 more
wiley   +1 more source

General inertial proximal stochastic variance reduction gradient for nonconvex nonsmooth optimization

Journal of Inequalities and Applications, 2023
In this paper, motivated by the competitive performance of the proximal stochastic variance reduction gradient (Prox-SVRG) method, a novel general inertial Prox-SVRG (GIProx-SVRG) algorithm is proposed for solving a class of nonconvex finite sum problems.
Shuya Sun, Lulu He
doaj   +1 more source

MCNP variance reduction overview [PDF]

, 1985
The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as
Booth, T. E., Hendricks, J. S.
core  

Neural variance reduction for stochastic differential equations

, 2023
Variance reduction techniques are of crucial importance for the efficiency of Monte Carlo simulations in finance applications. We propose the use of neural SDEs, with control variates parameterized by neural networks, in order to learn approximately ...
Hinds, P.D., Hinds, P. D., Tretyakov, M.V., Tretyakov, M. V.   +3 more
core   +1 more source

Deep Sequencing of FLT3‐ITD Enables Response Evaluation and Post‐Treatment Monitoring in Childhood AML: An Exploratory Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm, Bea Tornberg, Erik Delsing Malmberg, Henrik Hasle, Kristian Løvvik Juul‐Dam, Lars Palmqvist, Borhan R. Saeed, Giti Shah Barkhordar, Anastasia Soboli, Anna Staffas, Jonas Abrahamsson, Linda Fogelstrand   +11 more
wiley   +1 more source

Stochastic Variance Reduced Primal–Dual Hybrid Gradient Methods for Saddle-Point Problems

Mathematics
Recently, many stochastic Alternating Direction Methods of Multipliers (ADMMs) have been proposed to solve large-scale machine learning problems. However, for large-scale saddle-point problems, the state-of-the-art (SOTA) stochastic ADMMs still have high
Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu   +3 more
doaj   +1 more source

L2 Model Reduction and Variance Reduction

, 2002
In this contribution we examine certain variance properties of model reduction. The focus is on L2 model reduction, but some general results are also presented. These general results can be used to analyze various other model reduction schemes.
Ljung, Lennart,, Tjernström, Fredrik,
core   +1 more source

Online Variance Reduction with Mixtures

CoRR, 2019
Adaptive importance sampling for stochastic optimization is a promising approach that offers improved convergence through variance reduction. In this work, we propose a new framework for variance reduction that enables the use of mixtures over predefined sampling distributions, which can naturally encode prior knowledge about the data.
Zalán Borsos, Sebastian Curi, Kfir Yehuda Levy, Andreas Krause 0001   +3 more
openaire   +3 more sources

Time Toxicity in Wilms Tumor: Quantifying the Burden of Healthcare Interaction in the First Year After Diagnosis

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook, Veerain Gupta, Nicholas J. Clark, Vijay Rings, Lauren E. Corona, Douglass B. Clayton, Daniel J. Benedetti   +6 more
wiley   +1 more source