Results 61 to 70 of about 22,296,575 (338)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed +5 more
wiley +1 more source
ArraySurrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. To reduce this cost, SAEAs employ surrogate models—machine learning models that
Yuki Hanawa +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background We describe clinical and biologic characteristics of neuroblastoma in older children, adolescents, and young adults (OCAYA); describe survival outcomes in the post‐immunotherapy era; and identify if there is an age cut‐off that best discriminates outcomes.
Rebecca J. Deyell +14 more
wiley +1 more source
Deep Graph Learning-Based Surrogate Model for Inverse Modeling of Fractured Reservoirs
MathematicsInverse modeling can estimate uncertain parameters in subsurface reservoirs and provide reliable numerical models for reservoir development and management. The traditional simulation-based inversion method usually requires numerous numerical simulations,
Xiaopeng Ma +4 more
doaj +1 more source
Surrogate model for gravitational wave signals from comparable and large-mass-ratio black hole binaries [PDF]
Physical Review D, 2019 Gravitational wave signals from compact astrophysical sources such as those observed by LIGO and Virgo require a high-accuracy, theory-based waveform model for the analysis of the recorded signal.
N. Rifat +3 more
semanticscholar +1 more source
Universal Prediction Distribution for Surrogate Models [PDF]
SIAM/ASA Journal on Uncertainty Quantification, 2017 The use of surrogate models instead of computationally expensive simulation codes is very convenient in engineering. Roughly speaking, there are two kinds of surrogate models: the deterministic and the probabilistic ones. These last are generally based on Gaussian assumptions.
Ben Salem, Malek +3 more
openaire +5 more sources
MATSuMoTo: The MATLAB Surrogate Model Toolbox For Computationally Expensive Black-Box Global Optimization Problems [PDF]
, 2014 MATSuMoTo is the MATLAB Surrogate Model Toolbox for computationally expensive, black-box, global optimization problems that may have continuous, mixed-integer, or pure integer variables.
Mueller, Juliane
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Psychological safety (PS) is essential for teamwork, communication, and patient safety in complex healthcare environments. In pediatric oncology, interprofessional collaboration occurs under high emotional and organizational demands. Low PS may increase stress, burnout, and adverse events.
Alexandros Rahn +4 more
wiley +1 more source
Using machine learning surrogate modeling for faster QSP VP cohort generation
CPT: Pharmacometrics & Systems Pharmacology, 2023 Virtual patients (VPs) are widely used within quantitative systems pharmacology (QSP) modeling to explore the impact of variability and uncertainty on clinical responses.
Renée C. Myers +3 more
doaj +1 more source
Modelling, 2023 Complex engineering models are typically computationally demanding and defined by a high-dimensional parameter space challenging the comprehensive exploration of parameter effects and design optimization.
Corey Arndt +4 more
doaj +1 more source