Results 31 to 40 of about 717,161 (269)
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source
Analysis and Evaluation of Feature Selection and Feature Extraction Methods
Hand gestures are widely used in human-to-human and human-to-machine communication. Therefore, hand gesture recognition is a topic of great interest. Hand gesture recognition is closely related to pattern recognition, where overfitting can occur when ...
Rubén E. Nogales, Marco E. Benalcázar
doaj +1 more source
Stability of feature selection algorithm: A review
Feature selection technique is a knowledge discovery tool which provides an understanding of the problem through the analysis of the most relevant features.
Utkarsh Mahadeo Khaire, R. Dhanalakshmi
doaj +1 more source
Many strategies have been exploited for the task of feature selection, in an effort to identify more compact and better quality feature subsets. Such techniques typically involve the use of an individual feature significance evaluation, or a measurement of feature subset consistency, that work together with a search algorithm in order to determine a ...
Qiang Shen 0001, Ren Diao, Pan Su 0001
openaire +2 more sources
ABSTRACT Background Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, with an overall survival now surpassing 90% in developed countries. However, treatments are not without adverse effects. In this study, we apply the severe toxicity‐free survival (STFS) framework to determine the prevalence of 21 physician‐defined severe ...
Lane Collier +10 more
wiley +1 more source
Dual-Regularized Feature Selection for Class-Specific and Global Feature Associations
Understanding feature associations is vital for selecting the most informative features. Existing methods primarily focus on global feature associations, which capture overall relationships across all samples.
Chenchen Wang +4 more
doaj +1 more source
Feature selection plays an important role in the data mining process. It is needed to deal with the excessive number of features, which can become a computational burden on the learning algorithms. It is also necessary, even when computational resources are not scarce, since it improves the accuracy of the machine learning tasks, as we will see in the ...
Tarek Amr Abdallah +1 more
openaire +2 more sources
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
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
Hybrid Feature Selection Method for Tumor Gene Based on Spark [PDF]
In order to deal with the tumor gene data which grows rapidly with the development of microarray technology,and achieve the feature selection of tumor gene data,combined with integrated feature selection and mixed feature selection,a hybrid feature ...
WANG Lili,DENG Li,YU Yue,FEI Minrui
doaj +1 more source

