Results 91 to 100 of about 106,507 (280)
A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento +3 more
wiley +1 more source
SMOTEHashBoost: Ensemble Algorithm for Imbalanced Dataset Pattern Classification
Class imbalance occurs frequently in machine learning, particularly in binary classification tasks where the majority class has a significantly larger number of samples than the minority class.
Seema Yadav +4 more
doaj +1 more source
Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin +11 more
wiley +1 more source
Recurrent Hypothermia and Autonomic Dysfunction Secondary to Shapiro Syndrome
ABSTRACT A 44‐year‐old man presented with recurrent hypothermia, diaphoresis and hypertension. Extensive investigation for infectious, inflammatory, metabolic and endocrine aetiologies was negative. MR scan of the brain demonstrated no lesions but revealed callosal dysgenesis, consistent with Shapiro syndrome.
Naveen Kumar +3 more
wiley +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 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
An Efficient Deep Learning-Based Skin Cancer Classifier for an Imbalanced Dataset. [PDF]
Alam TM +7 more
europepmc +1 more source
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe +7 more
wiley +1 more source
The healthcare fraud detection field is constantly evolving and faces significant challenges, particularly when addressing imbalanced data issues. Previous studies mainly focused on traditional machine learning (ML) techniques, often struggling with ...
Rayene Bounab +3 more
doaj +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source

