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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 Primary lung carcinomas and bronchial carcinoid tumors (BC) are very rare malignancies in childhood. While typical BC and mucoepidermoid carcinomas are mostly low‐grade, localized tumors with a more favorable prognosis than in adults, necessitating avoidance of overtreatment, adenocarcinomas of the lung are often diagnosed at advanced disease ...
Michael Abele +19 more
wiley +1 more source
, 2019 This study reviews two different problems of routed wavelength assignment optical network which are; static network RWA in this type the connection requests already given in advance, and dynamic network RWA where the requests of connection randomly arrived.
Jan Žižka +2 more
openaire +4 more sources
Infinite Latent Feature Selection Technique for Hyperspectral Image Classification
Jurnal Elektronika dan Telekomunikasi, 2019 The classification process is one of the most crucial processes in hyperspectral imaging. One of the limitations in classification process using machine learning technique is its complexities, where hyperspectral image format has a thousand band that can
Tajul Miftahushudur +2 more
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Feature Redundancy Based on Interaction Information for Multi-Label Feature Selection
IEEE Access, 2020 Recent years, multi-label feature selection has gradually attracted significant attentions from machine learning, statistical computing and related communities and has been widely applied to diverse problems from music recognition to text mining, image ...
Wanfu Gao +3 more
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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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Results of the Childhood Cancer and Leukaemia Group's United Kingdom Relapsed Wilms Tumour Trial
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The United Kingdom relapsed Wilms tumour (UKW‐R) trial aimed to improve the historically low survival rates after relapse of Wilms tumour (WT) through a prospective national risk‐stratified protocol. The trial also evaluated efficacy and toxicity of high‐dose melphalan.
Sucheta J. Vaidya +10 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Adolescent siblings of children with cancer are at elevated risk for psychosocial problems. Unfortunately, various barriers such as limited family time and resources, conflicting schedules, and psychosocial staffing constraints at cancer centers hinder sibling access to support.
Christina M. Amaro +10 more
wiley +1 more source
Staging of Prostate Cancer Using Automatic Feature Selection, Sampling and Dempster-Shafer Fusion
Cancer Informatics, 2009 A novel technique of automatically selecting the best pairs of features and sampling techniques to predict the stage of prostate cancer is proposed in this study.
Sandeep Chandana +2 more
doaj
Pediatric Blood &Cancer, EarlyView.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