Results 131 to 140 of about 103,585 (306)
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
Dual generative adversarial networks based on regression and neighbor characteristics.
PLoS ONEImbalanced data is a problem in that the number of samples in different categories or target value ranges varies greatly. Data imbalance imposes excellent challenges to machine learning and pattern recognition.
Weinan Jia +4 more
doaj +1 more source
Integrating Data Selection and Extreme Learning Machine for Imbalanced Data
, 2015 Extreme Learning Machine (ELM) is one of the artificial neural network method that introduced by Huang, this method has very fast learning capability. ELM is designed for balance data. Common problems in real-life is imbalanced data problem.
Irawan, M. Isa +2 more
core +1 more source
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
ALDOA Promotes Glycolysis and NLRP3/GSDMD Pyroptosis to Accelerate ALS Progression
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is characterized by progressive motor neuron degeneration. Glycolytic dysregulation is implicated in disease progression, yet the underlying mechanisms remain unclear. This study investigates how Aldolase A (ALDOA) drives ALS progression through glycolysis‐mediated motor neuron pyroptosis.
Kaixin Yan +9 more
wiley +1 more source
Generative Oversampling Method for Imbalanced Data on Bearing Fault Detection and Diagnosis
, 2019 In this study, we developed a novel data-driven fault detection and diagnosis (FDD) method for bearing faults in induction motors where the fault condition data are imbalanced.
Lukowicz, Paul +10 more
core +1 more source
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
Shape Penalized Decision Forests for Imbalanced Data Classification
IEEE AccessClass imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set.
Rahul Goswami +4 more
doaj +1 more source
A Gaussian mixture based boosted classification scheme for imbalanced and oversampled data
, 2017 Dataset with imbalanced class distribution used to abate classification performance for most of the standard classifier learning algorithms. Moreover, some application area consists of scarcity of labeled training data where clustering is most prominent ...
Pal, Biprodip +3 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source