Results 241 to 250 of about 60,070 (303)

Ofatumumab in Myelin Oligodendrocyte Glycoprotein Antibody–Associated Disease: A Comparison With Rituximab

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the efficacy and safety of ofatumumab in patients with myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), and compare it with rituximab. Methods We conducted a single–center, observational study including 22 MOGAD patients treated with ofatumumab and 21 treated with rituximab.
Yuxin Fan   +5 more
wiley   +1 more source

A Nonparametric Approach to Practical Identifiability of Nonlinear Mixed Effects Models. [PDF]

open access: yesBull Math Biol
Cassidy T   +6 more
europepmc   +1 more source

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani   +10 more
wiley   +1 more source

Plasma pTau 217/β-amyloid 1-42 ratio for enhanced accuracy and reduced uncertainty in detecting amyloid pathology. [PDF]

open access: yesBrain
Benina N   +19 more
europepmc   +1 more source

Modelling the cost-effectiveness of interventions to treat or prevent neuropathic ulcers arising from leprosy: application to L-PRF. [PDF]

open access: yesCost Eff Resour Alloc
Ochalek J   +11 more
europepmc   +1 more source

Optimization on parametric model

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, 2018
Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with large number of weights consume considerable storage and memory bandwidth. To address this limitation, prun­ing is an effective way to compress neural networks with high accuracy.
Fenfen Huang, Wenbin Yao
openaire   +1 more source

Neuro-wavelet parametric modeling

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
This work describes Neuro-Wavelet Parametric Modeling, a neural-based technique to classify, model and forecast signals or problems which are functions of either time or space. The paper presents the base method and discusses on the selection of the optimal neuro-wavelet network. An industrial application is also presented.
COLLA, Valentina   +2 more
openaire   +4 more sources

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