Results 51 to 60 of about 796,511 (318)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with acute lymphoblastic leukemia (ALL) are at risk of severe outcomes from SARS‐CoV‐2 (SCV2). In the post‐pandemic context, where most children have been infected with SCV2, there are limited data on whether vaccination remains beneficial in children with ALL.
Janna R. Shapiro +11 more
wiley +1 more source
Hybrid feature selection based ScC and forward selection methods [PDF]
International Journal of Data and Network ScienceOperational data is always huge. A preprocessing step is needed to prepare such data for the analytical process so the process will be fast. One way is by choosing the most effective features and removing the others. Feature selection algorithms
Luai Al-Shalabi
doaj +1 more source
Optimal Feature Aggregation and Combination for Two-Dimensional Ensemble Feature Selection
Information, 2020 Feature selection is a way of reducing the features of data such that, when the classification algorithm runs, it produces better accuracy. In general, conventional feature selection is quite unstable when faced with changing data characteristics.
Machmud Roby Alhamidi, Wisnu Jatmiko
doaj +1 more source
Multi-objective squirrel search algorithm for EEG feature selection
, 2023 Feature selection plays a critical role in the application of Brain Computer Interface (BCI) systems. Many methods have been used to solve the feature selection problem, but they model it as a single-objective problem, considering only classification ...
Wen, Tao Wen +15 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm +11 more
wiley +1 more source
Special Issue “Algorithms for Feature Selection”
Algorithms, 2023 This Special Issue of the open access journal Algorithms is dedicated to showcasing cutting-edge research in algorithms for feature selection [...]
Muhammad Adnan Khan
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, 2017 Feature selection is used in many application areas relevant to expert and intelligent systems, such as machine learning, data mining, cheminformatics and natural language processing. In this study we propose methods for feature selection and features analysis based on Support Vector Machines (SVM) with linear kernels.
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Claudin‐6 has emerged as a promising immunotherapeutic target, yet protein‐level data in atypical teratoid/rhabdoid tumors (AT/RTs) have been inconsistent. We analyzed 36 well‐characterized AT/RT samples and found membranous claudin‐6 protein expression in 58% of cases, with striking enrichment in the molecular subgroup AT/RT‐TYR (100%) and ...
Victoria E. Fincke +4 more
wiley +1 more source
Entropy-based feature selection with applications to industrial internet of things (IoT) and breast cancer prediction [PDF]
Big Data and Computing VisionsFeature Selection (FS) is employed in the Machine Learning (ML) process to increase accuracy. Eliminating redundant and irrelevant variables while keeping the most important ones boosts the prediction capacity of the algorithms.
Ismail Mageed
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook +6 more
wiley +1 more source