Results 41 to 50 of about 848,965 (236)

Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim, Han Gil Seo, Roh‐Eul Yoo, Byung‐Mo Oh   +3 more
wiley   +1 more source

Information-Geometric Models in Data Analysis and Physics

Mathematics
Information geometry provides a data-informed geometric lens for understanding data or physical systems, treating data or physical states as points on statistical manifolds endowed with information metrics, such as the Fisher information.
D. Bernal-Casas, José M. Oller
doaj   +1 more source

Improving Speaker Recognition in Environmental Noise With Adaptive Filter

IEEE Access, 2022
Speaker recognition is challenging in real-world environments. Typically, studies approach noises only in an additive manner. However, real environments commonly present reverberating conditions that worsen speech processing.
Vinicius Almeida Dos Santos, Wemerson Delcio Parreira, Anita Maria Da Rocha Fernandes, Raul Garcia Ovejero, Valderi Reis Quietinho Leithardt   +4 more
doaj   +1 more source

Kernel Mean Shrinkage Estimators [PDF]

, 2016
A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principal component analysis, and it also forms the core inference step of modern ...
Fukumizu, Kenji, Gretton, Arthur, Muandet, Krikamol, Schölkopf, Bernhard, Sriperumbudur, Bharath   +4 more
core   +2 more sources

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

On the Complexity of Learning with Kernels [PDF]

, 2014
A well-recognized limitation of kernel learning is the requirement to handle a kernel matrix, whose size is quadratic in the number of training examples.
Cesa-Bianchi, Nicolò, Mansour, Yishay, Shamir, Ohad   +2 more
core   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

Relationship Between Neurologic Symptoms and Signs and FMR1 Genotype in Premutation Carriers

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Fragile X‐associated Tremor/Ataxia Syndrome (FXTAS) is the most severe late‐onset condition caused by a premutation in the FMR1 gene, characterized by expanded CGG triplet repeats of 55–200. Clinical presentations of FXTAS, including gait ataxia, kinetic tremor, cognitive decline, and rare Parkinsonism, are linked to ...
Flora Tassone, Freddy Chafota, Miguel E. Rentería, Randi J. Hagerman, Ellery Santos, Anna Atkinson, Nicholas G. Martin, Elsdon Storey, Danuta Z. Loesch   +8 more
wiley   +1 more source

Positive Definite Kernels in Machine Learning [PDF]

, 2009
This survey is an introduction to positive definite kernels and the set of methods they have inspired in the machine learning literature, namely kernel methods.
Cuturi, Marco
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source