Results 71 to 80 of about 30,987,372 (386)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Alveolar soft part sarcoma (ASPS) is a rare soft tissue sarcoma occurring most commonly in adolescence and young adulthood. Methods We present the clinical characteristics, treatments, and outcomes of patients with newly diagnosed ASPS enrolled on the Children's Oncology Group study ARST0332.
Jacquelyn N. Crane +11 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source
Ordinal classification for interval-valued data and interval-valued functional data
Expert Systems with ApplicationsThe aim of ordinal classification is to predict the ordered labels of the output from a set of observed inputs. Interval-valued data refers to data in the form of intervals. For the first time, interval-valued data and interval-valued functional data are considered as inputs in an ordinal classification problem.
Aleix Alcacer +2 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT A second allogeneic (allo‐)hematopoietic stem cell transplantation (HSCT2) is a potential curative option for pediatric patients with acute lymphoblastic leukemia (ALL) following relapse after first allogeneic transplantation (HSCT1), but its efficacy is limited by high relapse rates and transplant‐related toxicity in highly pretreated ...
Ava Momm +10 more
wiley +1 more source
DEA with Missing Data: An Interval Data Assignment Approach [PDF]
Journal of Optimization in Industrial Engineering, 2015 In the classical data envelopment analysis (DEA) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. In recent years, there are few researches on handling missing data.
Reza Kazemi Matin, Roza Azizi
doaj
PARTIAL LEAST SQUARES REGRESSION $PLS$ ON INTERVAL DATA
Revista de la Facultad de Ciencias, 2016 Uncertainty in the data can be considered as a numerical interval in which a variable can assume its possible values, this has been known as interval data. In this paper the $PLS$ regression methodology is extended to the case where explanatory, response
Carlos Alberto Gaviria-Peña +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background L‐asparaginase is a critical component in treatment protocols for pediatric acute lymphoblastic leukemia. Acute pancreatitis reactions can necessitate delays and, in some cases, discontinuation of L‐asparaginase, which compromises outcomes.
Edward J. Raack +39 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Malignant rhabdoid tumor of the kidney (MRTK) is a rare, aggressive tumor seen in young children. The optimal timing of resection for locally advanced tumors is not well‐defined. The purpose of this study is to evaluate modern oncologic outcomes and the impact of surgical timing. Methods A multicenter retrospective review was performed
Hannah N. Rinehardt +76 more
wiley +1 more source
New clustering methods for interval data [PDF]
Computational Statistics, 2006 Two new clustering methods are proposed for multivariate interval data. They are modifications of the dynamic \(k\)-clustering algorithm based on minimization of distances from elements of the cluster to its prototype (centre). The number \(k\) of clusters is fixed.
Chavent, Marie +3 more
openaire +3 more sources
Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2020 Background Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies.
Tapiwa Ganyani +6 more
semanticscholar +1 more source