Results 91 to 100 of about 2,067,646 (378)

Prediction and analysis of COVID-19 daily new cases and cumulative cases: times series forecasting and machine learning models [PDF]

open access: gold, 2022
Yanding Wang   +9 more
openalex   +1 more source

Pathogenic Germline PALB2 and RAD50 Variants in Patients With Relapsed Ewing Sarcoma

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Approximately 10% of patients with Ewing sarcoma (EwS) have pathogenic germline variants. Here, we report two cases: first, a novel germline pathogenic variant in partner and localizer of BRCA2 (PALB2) in a patient with a late EwS relapse. Its impact on homologous recombination is demonstrated, and breast cancer risk is discussed.
Molly Mack   +12 more
wiley   +1 more source

Effective Natural Language Processing Algorithms for Early Alerts of Gout Flares from Chief Complaints

open access: yesForecasting
Early identification of acute gout is crucial, enabling healthcare professionals to implement targeted interventions for rapid pain relief and preventing disease progression, ensuring improved long-term joint function.
Lucas Lopes Oliveira   +4 more
doaj   +1 more source

Improved Outcomes for Older Children, Adolescents, and Young Adults With Neuroblastoma in the Post‐Immunotherapy Era: An Updated Report From the International Neuroblastoma Risk Group

open access: yesPediatric 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

Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules [PDF]

open access: yes, 2013
Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally ...
Adya, Monica, Lusk, Edward J.
core   +1 more source

Characterizing Parental Concerns About Lasting Impacts of Treatment in Children With B‐Acute Lymphoblastic Leukemia

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background B‐acute lymphoblastic leukemia (B‐ALL) is the most common pediatric cancer, and while most children in high‐resource settings are cured, therapy carries risks for long‐term toxicities. Understanding parents’ concerns about these late effects is essential to guide anticipatory support and inform evolving therapeutic approaches ...
Kellee N. Parker   +7 more
wiley   +1 more source

Evaluating the Potential of Copulas for Modeling Correlated Scenarios for Hydro, Wind, and Solar Energy

open access: yesForecasting
The increasing global adoption of variable renewable energy (VRE) sources has transformed the use of forecasting, scenario planning, and other techniques for managing their inherent generation uncertainty and interdependencies.
Anderson M. Iung   +3 more
doaj   +1 more source

Clinical Characteristics and Prognostic Risk Factors for Pediatric B‐Cell Lymphoblastic Lymphoma: A Multicenter Retrospective Cohort Study for China Net Childhood Lymphoma

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu   +20 more
wiley   +1 more source

Comparative Analysis of Physics-Guided Bayesian Neural Networks for Uncertainty Quantification in Dynamic Systems

open access: yesForecasting
Uncertainty quantification (UQ) is critical for modeling complex dynamic systems, ensuring robustness and interpretability. This study extends Physics-Guided Bayesian Neural Networks (PG-BNNs) to enhance model robustness by integrating physical laws into
Xinyue Xu, Julian Wang
doaj   +1 more source

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