Results 71 to 80 of about 40,795 (265)

Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
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

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

open access: yesIEEE 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

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
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

Impact of imbalanced features on large datasets

open access: yesFrontiers 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

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
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

Classification Problem in Imbalanced Datasets

open access: yes, 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

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif   +17 more
wiley   +1 more source

The Gut–Heart Axis in Systemic Sclerosis: Evidence From a Large Prospective Early Disease Cohort

open access: yesArthritis Care &Research, EarlyView.
Objective Cardiac involvement significantly impacts prognosis in systemic sclerosis (SSc), highlighting the need for early risk stratification. Gastrointestinal (GI) symptoms are common and often manifest early. Emerging data suggest a link between GI and cardiac manifestations, possibly through shared mechanisms like dysautonomia.
Francesca R. Di Ciommo   +9 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
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

SMOTEHashBoost: Ensemble Algorithm for Imbalanced Dataset Pattern Classification

open access: yesIEEE Access
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

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