Imbalanced dataset - Open Access .click

Results 81 to 90 of about 106,507 (280)

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati +10 more
wiley +1 more source

UkM: A Novel Undersampling Method Using Modified k-Medoids Algorithm

IEEE Access
Learning from imbalanced data remains a persistent challenge in classification tasks, often resulting in biased model performance and poor generalization, particularly for the minority class.
Duygu Selin Turan
doaj +1 more source

Evidence of Iron Accumulation in Cerebral Adrenoleukodystrophy: A Potential Novel Disease Mechanism

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT In this first application of Quantitative Susceptibility Mapping Source Separation to cerebral adrenoleukodystrophy, we uncovered alterations in iron and myelin within lesions and normal appearing white matter. As validation, we demonstrate abnormal iron accumulation in those same compartments within primary brain tissue.
Christina L. Nemeth +8 more
wiley +1 more source

Sex Representation in US Stroke Clinical Trials: A Decade of Trends and Challenges

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Stroke remains a major cause of disability and mortality in the US, with significant sex‐based disparities, and females remain underrepresented in stroke clinical trials. We aimed to examine sex representation in US‐based stroke clinical trials, identify trial characteristics associated with higher female enrollment (≥ 50%), and ...
Chaitali Dagli +5 more
wiley +1 more source

Cracking the Code: Genotype–Phenotype Correlation Models in Sarcoglycanopathies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Sarcoglycanopathies are among the most severe limb‐girdle muscular dystrophies (LGMD), though milder presentations have been described. These diseases are primarily caused by missense variants, but the limited predictability of their effect on protein maturation, complex formation, and transport has hindered reliable genotype ...
Leonela Luce +72 more
wiley +1 more source

An Overview on the Advancements of Support Vector Machine Models in Healthcare Applications: A Review

Information
Support vector machines (SVMs) are well-known machine learning algorithms for classification and regression applications. In the healthcare domain, they have been used for a variety of tasks including diagnosis, prognosis, and prediction of disease ...
Rosita Guido +3 more
doaj +1 more source

Classification Problem in Imbalanced Datasets

, 2020
La classification est une tâche d'exploration de données. Elle vise à extraire des connaissances à partir de grands ensembles de données. Il existe deux types de classification. La première est connue sous le nom de classification complète, et elle est appliquée à des ensembles de données équilibrés. Cependant, lorsqu'elle est appliquée à des ensembles
Aouatef Mahani, Ahmed Riad Baba Ali
openaire +2 more sources

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +1 more source

Impact of imbalanced features on large datasets

Frontiers in Big Data
The exponential growth of image and video data motivates the need for practical real-time content-based searching algorithms. Features play a vital role in identifying objects within images. However, feature-based classification faces a challenge due to uneven class instance distribution. Ideally, each class should have an equal number of instances and
Waleed Albattah, Rehan Ullah Khan
openaire +3 more sources

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu +21 more
wiley +1 more source

classification
imbalanced data
fos: computer and information sciences

machine learning cs.lg
computer science - machine learning
machine learning

class imbalance
4. education
oversampling