Results 201 to 210 of about 7,158 (259)

Unsupervised clustering of electroclinical features in temporal lobe epilepsy: A data‐driven approach

Epileptic Disorders, EarlyView.
Abstract Objective To identify clinically meaningful patterns in ictal electroclinical features of focal epilepsy using a data‐driven, unsupervised learning approach, and to assess whether such patterns can localize and lateralize the epileptogenic zone (EZ) more accurately than conventional electroclinical interpretation.
Maria Vlachou, Bernadett Molnár, Helene Kaas, Jesper Tveit, Harald Aurlien, Martin Ejler Fabricius, Guido Rubboli, Lars Hageman Pinborg, Sándor Beniczky   +8 more
wiley   +1 more source

An Exploration of Machine Learning Methods in Human Biomonitoring. [PDF]

Int J Environ Res Public Health
Singh K, Bi J, Musende M, Collins SP, Borghese MM, Hu JMY, Pollock T, St-Amand A, Hennessy D, Buckeridge DL.   +9 more
europepmc   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

An improved global database and model of plant available soil phosphorus. [PDF]

Sci Data
McDowell RW, Noble ADL, Doscher C, Helfenstein J.   +3 more
europepmc   +1 more source

Inter‐Material Transfer Learning for Accelerated Nanofluid Heat Transfer Prediction: A Machine Learning Approach for Energy Systems

Energy Science &Engineering, EarlyView.
This study presents an inter‐material transfer learning framework for nanofluid heat transfer prediction in energy systems. By leveraging knowledge from Al2O3‐water data, the model accurately predicts hybrid Al2O3‐TiO2 nanofluid performance with only 20 simulations, achieving R2 = 0.985 and reducing computational requirements by 78. ABSTRACT This paper
Soumaya Hadj Salah, Aymen Ochi, Sonia Bezi   +2 more
wiley   +1 more source

Nontargeted screening identifies mixtures of environmental pollutants that are associated with perturbations to amino acid and fatty acid metabolic pathways during early pregnancy. [PDF]

Environ Int
Pedersen AF, Petrick LM, Roth K, Yang Z, Sitarik AR, Maroli A, Dolios G, Carignan C, Goodrich JM, Kerver JM, Petriello M.   +10 more
europepmc   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

Energy Science &Engineering, EarlyView.
A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti, Jamal Dabbagh, Jhila Nasiri Reveshti, Karim Farajeyan Bonab, Farid Hosseini Mansoub   +4 more
wiley   +1 more source

Identifying unmeasured heterogeneity in microbiome data via quantile thresholding (QuanT). [PDF]

Microbiome
Lu J, Satten GA, Meyer KA, Launer LJ, Ling W, Zhao N.   +5 more
europepmc   +1 more source

Legacy effects of locally extinct flagship species on protected areas

Frontiers in Ecology and the Environment, EarlyView.
Protected areas (PAs) are often established to conserve flagship megafauna so as to mobilize political support and secure sustained conservation investment, with the expectation that flagship‐centered governance will also protect habitat. Despite such efforts, flagship species can experience extirpation, raising a fundamental question: do conservation ...
Rachakonda Sreekar, James EM Watson, Jiajia Liu, Aakash Lamba, Hoong Chen Teo, Jun Ying Lim, Yiwen Zeng   +6 more
wiley   +1 more source

Pricing strategies of the tobacco companies in response to cigarette excise tax increases in Montenegro. [PDF]

PLoS One
Čizmović M, Mugoša A, Vukčević M, Vulović V.   +3 more
europepmc   +1 more source