Results 41 to 50 of about 774,252 (269)

Early Body Mass Index z‐Score Change and Resolution of Severe Malnutrition in Children With Sickle Cell Anemia in a Low‐Income Setting: A Prospective Single‐Arm Extension Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with sickle cell anemia (SCA) in low‐income settings are at risk of severe malnutrition, but optimal nutritional management has not been established. We evaluated an intensified ready‐to‐use therapeutic food (RUTF) regimen in children with persistent severe malnutrition after initial treatment and assessed whether early ...
Safiya Gambo, Shehu Umar Abdullahi, Hassan Adam Murtala, Halima Kabir, Khadija A. Shamsu, Sari A. Acra, Virginia A. Stallings, Mark Rodeghier, Michael R. DeBaun, Lauren J. Klein   +9 more
wiley   +1 more source

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, Hallie Coltin, Sylvia Cheng, Lucie Lafay‐Cousin, Vanan Issai Magimairajan, Craig Erker, Stéphanie Vairy, Lynette Bowes, Adam Fleming, Donna Johnston, Sarah McKillop, Roona Sinha, Julie Bennett, Christina Coleman, Laura Wheaton, Shayna Zelcer, Samuele Renzi, Thai Hoa Tran   +17 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 Visions
Feature 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
doaj   +1 more source

Feature Selection in Texts

, 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   +3 more sources

Comparative Drug Response Profiling in Neuroblastoma Cell Lines and Patient‐Derived Tumor Organoids

Pediatric Blood &Cancer, EarlyView.
ABSTRACT High‐risk neuroblastoma remains a leading cause of pediatric cancer mortality, and improved preclinical models are needed to guide therapeutic developments. We screened seven high‐risk neuroblastoma cell lines and three patient‐derived tumor organoids with 528 compounds alongside bone marrow controls, and compared them with external datasets ...
Krzysztof Wierbiłowicz, Se Whee Sammy Park, Aironas Los, Ernest Liu, Nona Struyf, Tom Erkers, Sören Lehmann, Jan J. Molenaar, Jakob Stenman, Olli Kallioniemi, Päivi Östling, Brinton Seashore‐Ludlow, Kasper Karlsson   +12 more
wiley   +1 more source

Binary Fox Optimization Algorithm for Feature Selection

Cybernetics and Information Technologies
There is an urgent need for algorithms capable of improving the selection of appropriate features that directly affect the improvement process of the algorithm’s accuracy efficiently. Therefore, in this paper, a new feature selection algorithm for binary
Mohammed Athraa Jasim, Ghathwan Khalil Ibrahim, Yusof Yuhanis   +2 more
doaj   +1 more source

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, Chaeriah Bin Ali Wael, Teguh Praludi   +2 more
doaj   +1 more source

Attack Transferability Against Information-Theoretic Feature Selection

IEEE Access, 2021
Machine learning (ML) is vital to many application-driven fields, such as image and signal classification, cyber-security, and health sciences. Unfortunately, many of these fields can easily have their training data tampered with by an adversary to ...
Srishti Gupta, Roman Golota, Gregory Ditzler   +2 more
doaj   +1 more source

Feature Selection by Reordering

, 2005
Feature selection serves for both reduction of the total amount of available data (removing of valueless data) and improvement of the whole behavior of a given induction algorithm (removing data that cause deterioration of the results). A method of proper selection of features for an inductive algorithm is discussed.
Jiřina, M. (Marcel), Jiřina jr., M.
openaire   +4 more sources

Retrospective Analysis of Donor Lymphocyte Infusions in Pediatric Patients With Mixed Chimerism After Hematopoietic Stem Cell Transplantation

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, Sebastian Michaelis, Michaela Döring, Thomas Eichholz, Ursula Holzer, Martin Ebinger, Tim Flaadt, Rupert Handgretinger, Peter Lang, Jan Frederic Weller, Markus Mezger   +10 more
wiley   +1 more source