Results 41 to 50 of about 22,758,962 (282)
Central Nervous System Tumors Among Infants in Canada: A Report From CYP‐C
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) tumors in infants are rare, pose unique clinical challenges, and lack large‐scale evidence‐based data to guide management. This study seeks to describe CNS tumors in Canadian infants and to compare their outcomes with those of older children.
Samuel Sassine +17 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Survivors of pediatric brain tumors (PBTs) can experience long‐term social difficulties, impacting quality of life. Beyond medical and environmental factors, family psychosocial risk may play a role in social outcomes by shaping the caregiving environment and may provide intervention options.
Renske H. Houben +4 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Allogeneic hematopoietic stem cell transplantation (alloHSCT) is an essential therapy for several malignant and nonmalignant diseases, but relapse and graft loss remain the principal threats to its success. Routine monitoring of chimerism and minimal residual disease (MRD) enables early detection of imminent recurrence and guides ...
Carmen Junk +10 more
wiley +1 more source
LC an effective classification based association rule mining algorithm [PDF]
Classification using association rules is a research field in data mining that primarily uses association rule discovery techniques in classification benchmarks.
Mahmood, Qazafi
core +3 more sources
Pediatric Idiopathic Multicentric Castleman Disease Is Often Severe But Responsive to Siltuximab
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Idiopathic multicentric Castleman disease (iMCD) is a potentially fatal immunologic disorder marked by widespread lymphadenopathy and inflammation. Siltuximab, an interleukin‐6 (IL‐6) inhibitor, is the only FDA‐approved treatment for adult patients with iMCD.
Bridget Austin +17 more
wiley +1 more source
Robust rule-based prediction [PDF]
, 2006 This paper studies a problem of robust rule-based classification, i.e. making predictions in the presence of missing values in data. This study differs from other missing value handling research in that it does not handle missing values but builds a rule
Li, Jiuyong, Li, J.
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Numerous international studies have reported declines in new cancer diagnoses, delayed diagnoses and disruptions in cancer treatment following the implementation of COVID‐19 pandemic public health measures, raising concerns that these effects may ultimately contribute to increased cancer mortality.
Friederike Erdmann +8 more
wiley +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
New unsupervised hybrid classifier based on the fuzzy integral: applied to natural textured images
IET Computer Vision, 2013 This study presents a new unsupervised hybrid classifier for natural texture identification in aerial images. The proposed strategy combines through the fuzzy integral (FI) six well‐tested base supervised classifiers.
María Guijarro +4 more
doaj +1 more source
Neighborhood Granule Classifiers
Applied Sciences, 2018 Classifiers are divided into linear and nonlinear classifiers. The linear classifiers are built on a basis of some hyper planes. The nonlinear classifiers are mainly neural networks. In this paper, we propose a novel neighborhood granule classifier based
Hongbo Jiang, Yumin Chen
doaj +1 more source