Results 251 to 260 of about 517,784 (313)

Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec, Elif Everest, Melih Tutuncu, Ugur Bilge, Sabahattin Saip, Ugur Uygunoglu, Aksel Siva   +6 more
wiley   +1 more source

The choice of time scales in survival analysis has implications: calendar time versus patients' time-to-event. [PDF]

BMC Med Res Methodol
Vilsmeier J, Büchele G, Rehm M, Unseld T, Rothenbacher D, Beyersmann J.   +5 more
europepmc   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

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, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Smooth transformation models for survival analysis: A tutorial using R. [PDF]

Stat Methods Med Res
Siegfried S, Tamási B, Hothorn T.
europepmc   +1 more source

A global parametric rain model for landfalling tropical cyclones: a case study for the U.S. [PDF]

Nat Hazards (Dordr)
Lau KH, Czernichow S, Sparks N, Toumi R.
europepmc   +1 more source

A benchmarking of genomic selection models for predicting grain-yield related traits using haplotype-based and genome-wide association study-based markers in rice. [PDF]

Plant Genome
Hu X, Xian L, Cao G, Liu S, Wang D, Che Y, Huang W, Lin Y, He L.   +8 more
europepmc   +1 more source

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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, L. M. Reyneri, SGARBI, MIRKO   +2 more
openaire   +4 more sources

Identification in Parametric Models

Econometrica, 1971
A theory of identification is developed for a general stochastic model whose probability law is determined by a finite number of parameters. It is shown under weak regularity conditions that local identifiability of the unknown parameter vector is equivalent to nonsingularity of the information matrix.
openaire   +2 more sources

A parametric yield model

Journal of Electronic Testing, 1995
Assuming that the distribution of path delays introduced by variations in the manufacturing process is exponential instead of gaussian, the interdependence problem between delay-optimization of synthesized networks and parametric yield has been revisited. The result confirms the claim of Williams, Underwood, and Mercer.
openaire   +1 more source