Results 91 to 100 of about 282,377 (316)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Accessing brain magnetic resonance imaging (MRI) can be challenging, especially for underserved patients, which may lead to disparities in neurological diagnosis. Method This mixed‐methods study enrolled adults with one of four neurological disorders: mild cognitive impairment or dementia of the Alzheimer type, multiple sclerosis ...
Maya L. Mastick +19 more
wiley +1 more source
COMPARING THE EFFECTIVENESS OF RANK CORRELATION STATISTICS [PDF]
Rank correlation is a fundamental tool to express dependence in cases in which the data are arranged in order. There are, by contrast, circumstances where the ordinal association is of a nonlinear type.
Agostino Tarsitano
core
Structured Low-rank Approximation as a Rational Function Minimization [PDF]
, 2012 Many problems of system identification, model reduction and signal processing can be posed and solved as a structured low-rank approximation problem (SLRA).
Markovsky, Ivan, Usevich, Konstantin
core
Planarity ranks for varieties of equationally noetherian semigroups [PDF]
Известия Саратовского университета. Новая серия: Математика. Механика. ИнформатикаThe problem of describing semigroup varieties with finite planarity rank is researched. In addition to the previously obtained results the author finds new countable infinite series of semigroup varieties with finite planarity rank.
Solomatin, Denis Vladimirovich
doaj +1 more source
Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati +10 more
wiley +1 more source
Low-rank matrix approximation with weights or missing data is NP-hard [PDF]
Weighted low-rank approximation (WLRA), a dimensionality reduction technique for data analysis, has been successfully used in several applications, such as in collaborative filtering to design recommender systems or in computer vision to recover ...
GILLIS, Nicolas, GLINEUR, François
core
FDG‐PET Associations With Disease Severity and Outcomes in NMDA‐Receptor IgG Autoimmune Encephalitis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Patients with N‐methyl‐D‐aspartate (NMDA) receptor‐immunoglobulin G (IgG) autoimmune encephalitis (NMDAR‐IgG AE) demonstrate occipital lobe hypometabolism on baseline brain fluorodeoxyglucose‐positron emission tomography (bFDG‐PET).
Jonathan K. Lee +7 more
wiley +1 more source
Approximate low-rank factorization with structured factors
, 2010 An approximate rank revealing factorization problem with structure constraints on the normalized factors is considered. Examples of structure, motivated by an application in microarray data analysis, are sparsity, nonnegativity, periodicity, and ...
Niranjan, Mahesan, Markovsky, Ivan
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Posterior Cortical Atrophy in the Asia‐Pacific: A Report From the PCA Asian Workgroup
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Posterior Cortical Atrophy (PCA) is a distinct dementia syndrome primarily affecting spatial abilities and visual processing. It is associated with degeneration in the posterior part of the brain. PCA is subclassified into PCA‐pure and PCA‐plus syndromes based on consensus criteria.
Yuttachai Likitjaroen +11 more
wiley +1 more source
Finding a rank-maximizing matrix block
, 1966 An algorithm is developed for the following problem: Given three matrices of respective dimensions sXs, sXt, and tXs, to find a tXt matrix such that the (s+t)X(s+t) matrix formed from the four blocks has maximum ...
Goldman, A. J.; Newman, M.
core +1 more source