Results 91 to 100 of about 222,810 (285)
This study aimed to evaluate the prognostic value of ELN2017 in predicting survival outcomes and to assess the impact of clinical and molecular factors such as age, FLT3 and NPM1 mutations, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT).
Mobina Shrestha +4 more
wiley +1 more source
Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model
Unsupervised learning on imbalanced data is challenging because, when given imbalanced data, current model is often dominated by the major category and ignores the categories with small amount of data.
Dai, Zhenwen +3 more
core
Aging Is a Key Driver for Adult Acute Myeloid Leukemia
Acute myeloid leukemia (AML) is a classical age‐related hematologic malignancy, and a key driver of AML is aging, which profoundly regulates intrinsic factors such as genomic instability, epigenetic reprogramming, and metabolic dysregulation, and alters bone marrow microenvironment.
Rong Yin, Haojian Zhang
wiley +1 more source
A comprehensive survey on imbalanced data learning
Abstract With the expansion of data availability, machine learning (ML) has achieved remarkable breakthroughs in both academia and industry. However, imbalanced data distributions are prevalent in various types of raw data and severely hinder the performance of ML by biasing the decision-making processes.
Gao, Xinyi +7 more
openaire +4 more sources
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
Whole‐Body Pattern of Muscle Degeneration and Progression in Sarcoglycanopathies
ABSTRACT Objective To characterize whole‐body intramuscular fat distribution pattern in patients with sarcoglycanopathies and explore correlations with disease severity, duration and age at onset. Methods Retrospective, cross‐sectional, multicentric study enrolling patients with variants in one of the four sarcoglycan genes who underwent whole‐body ...
Laura Costa‐Comellas +39 more
wiley +1 more source
Integrative machine learning approach for multi-class SCOP protein fold classification [PDF]
Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP classification, most discriminative machine learning suffers the well-known ‘
Deville, Y, Gilbert, D, Tan, A C
core
Effects of Biological Sex and Age on Cerebrospinal Fluid Markers—A Retrospective Observational Study
ABSTRACT Objective Cerebrospinal fluid (CSF) analysis is a key diagnostic tool for neurological diseases. To date, only a few studies have investigated in larger cohorts the effect of age and biological sex on diagnostic markers extracted from CSF. Methods For this retrospective observational study, 4163 CSF findings (2012–2020) were evaluated.
Isabel‐Sophie Hafer +3 more
wiley +1 more source
ABSTRACT Background SOX1 antibody‐positive paraneoplastic neurological syndromes (PNS) exhibit significant population‐specific clinical heterogeneity. While Western cohorts predominantly manifest Lambert‐Eaton myasthenic syndrome (65%–80%), comprehensive clinical characterization and treatment response data in Asian populations remain critically ...
Jin‐Long Ye +11 more
wiley +1 more source
Classification performance assessment for imbalanced multiclass data
The evaluation of diagnostic systems is pivotal for ensuring the deployment of high-quality solutions, especially given the pronounced context-sensitivity of certain systems, particularly in fields such as biomedicine.
Jesús S. Aguilar-Ruiz, Marcin Michalak
doaj +1 more source

