Results 101 to 110 of about 1,259,133 (314)

Online feature selection for model-based reinforcement learning [PDF]

, 2013
30th International Conference on Machine Learning, ICML 2013PART 1498 ...
Li, Zhuoru, Tze-Yun LEONG,, Nguyen, Trung Thanh, Leong, T.-Y., Silander, T., Li, Z., Nguyen, T.T., Silander, Tomi   +7 more
core  

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

Intelligent pavement management: a machine learning framework for condition classification and maintenance prioritization

Scientific Reports
Efficient pavement maintenance requires reliable classification of pavement condition and clear prioritization of interventions. This study develops and benchmarks a multi-model machine learning framework for pavement condition classification in both ...
Bhoomika Gupta, Mannya Agrawal, Preeti Narooka, Deepak Panwar, Sanchit Anand   +4 more
doaj   +1 more source

Machine Learning [PDF]

The Journal of Physical Chemistry Letters, 2018
William F. Schneider, Hua Guo
openaire   +6 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

Climate data selection for multi-decadal wind power forecasts

Environmental Research Letters
Reliable wind speed data is crucial for applications such as estimating local (future) wind power. Global climate models (GCMs) and regional climate models (RCMs) provide forecasts over multi-decadal periods.
Sofia Morelli, Nina Effenberger, Luca Schmidt, Nicole Ludwig   +3 more
doaj   +1 more source

Deterministic Uncertainty Estimation for Multi-Modal Regression With Deep Neural Networks

IEEE Access
Prediction interval (PI) is a common method to represent predictive uncertainty in regression by deep neural networks. This paper proposes an extension of the prediction interval by using a union of disjoint intervals. Since previous PI methods assumed a
Jaehak Cho, Jae Myung Kim, Seungyub Han, Jungwoo Lee   +3 more
doaj   +1 more source

Longitudinal Assessment of Biomarkers in ALS: Discriminative Biomarkers for Disease Progression and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the association and discriminative performance of serum biomarkers with clinical disease progression and survival in patients with amyotrophic lateral sclerosis (ALS). Methods This retrospective study, conducted at Houston Methodist Hospital, Houston, TX, used longitudinal serum samples collected between January 2018 and ...
David R. Beers, Yueh‐Yun Lin, Jason R. Thonhoff, Aaron D. Thome, Alireza Faridar, Weihua Zhao, Shixiang Wen, Stanley H. Appel   +7 more
wiley   +1 more source

Deep Learning‐Based Postprocessing to Enhance Subseasonal Soil Moisture Forecasts Over Europe

Journal of Geophysical Research: Machine Learning and Computation
Accurate forecasts on subseasonal (S2S) timescales are essential for the preparation and mitigation of the impacts of high‐impact events, such as flash droughts.
Noelia Otero, Atahan Özer, Jackie Ma
doaj   +1 more source

Review on the Advancements in Wind Turbine Blade Inspection: Integrating Drone and Deep Learning Technologies for Enhanced Defect Detection

IEEE Access
The increasing demand for wind power requires more frequent inspections to identify defects in the Wind Turbine Blades (WTBs). These defects, if not detected, can compromise the structural integrity and safety of wind turbines.
Majid Memari, Praveen Shakya, Mohammad Shekaramiz, Abdennour C. Seibi, Mohammad A. S. Masoum   +4 more
doaj   +1 more source