Results 61 to 70 of about 893,007 (263)
ABSTRACT Objectives The association between exposure to dinutuximab beta (DB) and event‐free survival (EFS) or overall survival (OS) of neuroblastoma patients was assessed using data collected during three clinical trials (five cohorts). Methods A systematic review (March 2026) was conducted to identify relevant studies (prospective; registered DB ...
Przemysław Holko +19 more
wiley +1 more source
Looking elsewhere: improving variational Monte Carlo gradients by importance sampling
Neural-network quantum states (NQSs) offer a powerful and expressive ansatz for representing quantum many-body wave functions. However, their training via Variational Monte Carlo (VMC) methods remains challenging.
Antoine Misery +3 more
doaj +1 more source
ABSTRACT Background Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver‐facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note‐taking features to support ...
Micah A. Skeens +4 more
wiley +1 more source
The Bayesian Causal Effect Estimation Algorithm
Estimating causal exposure effects in observational studies ideally requires the analyst to have a vast knowledge of the domain of application. Investigators often bypass difficulties related to the identification and selection of confounders through the
Talbot Denis +2 more
doaj +1 more source
ABSTRACT Background Survival after relapse in pediatric acute myeloid leukemia (AML) remains poor, highlighting the critical importance of identifying prognostic factors to guide optimal relapse management. Methods We investigated the prognostic impact of multiparameter flow cytometry (MFC) measurable residual disease (MRD) in 188 patients with first ...
Camilla Poulsen +21 more
wiley +1 more source
Variance Reduction Optimization Algorithm Based on Random Sampling [PDF]
The stochastic gradient descent (SGD) algorithms have been applied to machine learning and deep learning due to their superior performance. However, SGD requires the stochastic gradient of a single sample to approximate the full gradient of all samples ...
GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang
doaj +1 more source
ABSTRACT Hemophilic arthropathy remains the leading morbidity in hemophilia despite modern prophylaxis, and early joint damage may be missed by routine exams. This study explored T2* MRI as a noninvasive biomarker of hemosiderin deposition in pediatric hemophilia.
Jessica Garcia +6 more
wiley +1 more source
Stochastic Variance Reduced Primal–Dual Hybrid Gradient Methods for Saddle-Point Problems
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 +3 more
doaj +1 more source
A variance-reduction strategy for the sensitivity of βeff [PDF]
The Monte Carlo computation of the GPT-based sensitivity of the effective delayed neutron fraction βeff to nuclear data proves to be quite difficult to converge due to the small amount of delayed neutrons that are sampled in k-eigenvalue calculations ...
Jinaphanh Alexis, Zoia Andrea
doaj +1 more source
ABSTRACT Purpose Despite 5‐year survival rates of over 90% among children and adolescents/young adults (CAYAs) with classic Hodgkin lymphoma (cHL), 15%–20% relapse after frontline therapy. Prior analysis of frontline Children's Oncology Group (COG) clinical trials demonstrated that, despite similar rates of relapse, non‐Hispanic Black (NHB) and ...
Mallorie B. Heneghan +14 more
wiley +1 more source

