Results 71 to 80 of about 2,058,652 (297)

Uncovering Inequities: The Role of Social Determinants of Health in Hospitalized Adolescents and Young Adults With Heavy Menstrual Bleeding

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Heavy menstrual bleeding (HMB) is a common condition among adolescents and young adults (AYAs) and is the leading cause of iron deficiency anemia (IDA) in this population. Growing evidence suggests that social determinants of health (SDOH) influence menstrual bleeding patterns, access to care, and treatment. However, no studies have
Maria Carter‐Febres, Cristina Tarango, Ashley Childress, Chunyan Liu, Evan Thomas, Jennifer Pomales, Eric S. Mullins   +6 more
wiley   +1 more source

Energy Conservation in Wireless Sensor Networks Using Partly-Informed Sparse Autoencoder

IEEE Access, 2019
The energy in wireless sensor networks is considered a scarce commodity, especially in scenarios where it is difficult or impossible to provide supplementary energy sources once the initially available energy is used up.
Babajide O. Ayinde, Abdulaziz Y. Barnawi
doaj   +1 more source

Training set feature ranking, by information gain.

, 2014
Training set feature ranking, by information gain.
Qing Zhang (1802), Hong Yu (6528)
core   +1 more source

Feature importance ranking when classifying NPC vs. CRS.

, 2022
Feature importance ranking when classifying NPC vs. CRS.
Yuge Li (13511948), Ruxu Du (4558435), Jinyang Du (11175324), Guiyuan Peng (13767117), Yong Zhong (464992), Qi Liu (33068), Xuefang Wang (215231)   +6 more
core   +1 more source

Association Between Individualized Education for Kidney Replacement Therapy Modality Selection and Peritoneal Dialysis Initiation: A Cross‐Sectional Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito, Ryuichi Yoshimura, Takaki Yamauchi, Yuta Funakoshi, Hirotaka Sonoda, Seiji Kobayashi, Hiroyuki Terawaki, Takafumi Ito   +7 more
wiley   +1 more source

A Novel Preprocessing Approach Applying Pairwise Differences of Opposite Samples for Improved Interpretability in Binary Medical Classification

IEEE Access
Interpretability is crucial for the clinical adoption of machine learning, as healthcare providers require transparent decision-making processes to trust predictive tools effectively. Traditional feature selection methods often struggle to capture subtle
Daniel Pordeus, Joao Alexandre Lobo Marques, Roberto Coury Pedrosa, Joao Paulo do Vale Madeiro   +3 more
doaj   +1 more source

A Combination of Traditional and Polarimetric Features for Oil Spill Detection Using TerraSAR-X

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
Synthetic aperture radar (SAR) images are operationally used for the detection of oil spills in the marine environment, as they are independent of sun light and weather-induced phenomena.
Suman Singha, Rudolf Ressel, Domenico Velotto, Susanne Lehner   +3 more
doaj   +1 more source

Effect of DFPP on Ferroptosis in Peripheral Blood CD14+ Monocytes of Hyperlipidemic Patients Involving the ACSL4/LPCAT3/ALOX5 Pathway

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Hyperlipidemia is a major risk factor for atherosclerotic cardiovascular disease (ASCVD). Although statins are the cornerstone of lipid‐lowering therapy, their use may be limited in some patients by adverse effects. This study evaluated the possible impact of non‐drug treatment using double‐filtration plasmapheresis (DFPP) on CD14+
Yun Cheng, Lan Li, Qingmei Yang, Meipeng Wu   +3 more
wiley   +1 more source

Feature Selection with the Boruta Package

Journal of Statistical Software, 2010
This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm.
Miron B. Kursa, Witold R. Rudnicki
doaj  

D-HGFS: A Hybrid Greedy Forward Selection Framework for Robust Diabetes Prediction on Imbalanced Datasets

Future Internet
Diabetes-prediction models based on machine learning (ML) are often affected by inconsistent feature importance rankings. Different feature-selection algorithms emphasize different data characteristics and produce divergent ranked feature sets.
Rashed Alsakarnah, Mohammad Masoud
doaj   +1 more source