Results 91 to 100 of about 3,865,632 (281)

Spectral Methods for Learning Multivariate Latent Tree Structure [PDF]

, 2011
This work considers the problem of learning the structure of multivariate linear tree models, which include a variety of directed tree graphical models with continuous, discrete, and mixed latent variables such as linear-Gaussian models, hidden Markov ...
Anandkumar, Animashree, Chaudhuri, Kamalika, Hsu, Daniel, Kakade, Sham M., Song, Le, Zhang, Tong   +5 more
core   +1 more source

A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives SLC4A4 encodes electrogenic sodium bicarbonate cotransporter NBCe1, prominently expressed in kidney and brain. Recessive loss‐of‐function variants in SLC4A4 cause proximal renal tubular acidosis, no brain edema. In the brain, NBCe1 is expressed by astrocytes, where it regulates pH and mediates astrocyte volume changes.
Quinty Bisseling, Mark D. Parker, Sven Kerst, Richard A. Pasternack, Jacob Tondreau, Marjolein Breur, Gemma M. van Rooijen‐van Leeuwen, Davide Tonduti, Ettore Salsano, Alejandra Darling, Joanna A. E. van Wijk, Susanna Törnroth‐Horsefield, Marianna Bugiani, Petra J. W. Pouwels, Quinten Waisfisz, Marjo S. van der Knaap, Rogier Min   +16 more
wiley   +1 more source

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi, Katharine Lee, Kerry C. Nix, Miguel Menchaca, Xiwei Shé, Lorelei Santa Maria, Wei Wu, Zihuai He, Fiona M. Baumer   +8 more
wiley   +1 more source

Optimization of Active Learning Strategies for Causal Network Structure

Mathematics
Causal structure learning is one of the major fields in causal inference. Only the Markov equivalence class (MEC) can be learned from observational data; to fully orient unoriented edges, experimental data need to be introduced from external intervention
Mengxin Zhang, Xiaojun Zhang
doaj   +1 more source

Structured Apprenticeship Learning [PDF]

, 2012
We propose a graph-based algorithm for apprenticeship learning when the reward features are noisy. Previous apprenticeship learning techniques learn a reward function by using only local state features. This can be a limitation in practice, as often some features are misspecified or subject to measurement noise.
Boularias, A., Kroemer, O., Peters, J.
openaire   +2 more sources

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

A New Algorithm for Learning Large Bayesian Network Structure From Discrete Data

IEEE Access, 2019
Learning the structure of Bayesian networks (BNs) from high dimensional discrete data is common nowadays but a challenging task, due to the large parameter space, the acyclicity constraint placed on the graphical structures and the difficulty in ...
Weiping Zhang, Ziqiang Xu, Yu Chen, Jing Yang   +3 more
doaj   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento, Daniela F. Santos, Tuane C. R. G. Vieira, Tiago F. Outeiro   +3 more
wiley   +1 more source

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas

Entropy
Learning dependence graphs from multivariate continuous data is challenging when marginal distributions are heterogeneous, since likelihood-based nonparametric scores can be sensitive to smoothing choices and can confound marginal irregularities ...
Luiz Desuó Neto, Henrique de Oliveira Caetano, Matheus de Souza Sant’Anna Fogliatto, Carlos Dias Maciel   +3 more
doaj   +1 more source

Advancing Age Modulates Associations Between Cognitive Impairment and Brain Volumes in Early MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Cognitive impairment is common in multiple sclerosis (MS), but manifestations following the first demyelinating event are relatively unexplored. We investigated cross‐sectional associations between magnetic resonance imaging (MRI)–derived brain volumes and the presence of cognitive impairment outcomes five years after the first ...
Piriyankan Ananthavarathan, Marco Pitteri, Michael Foster, Sara Collorone, Sara Salama, Elisa Colato, Ferran Prados, Baris Kanber, Marios Yiannakas, Claudia A. M. Gandini Wheeler‐Kingshott, Indran Davagnanam, Frederik Barkhof, Declan Chard, Olga Ciccarelli, Ahmed Toosy   +14 more
wiley   +1 more source