Results 181 to 190 of about 62,585 (293)

An algorithm for seizure detection in rodents

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky, Gerben van Hameren, Itai Weissberg, Pooyan Moradi, Ofer Prager, Alaa Abu Ahmad, Lior Schori, Albert Becker, Yaniv Zigel, Alon Friedman   +9 more
wiley   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Joint mixed-effects models for causal inference in clustered network-based observational studies. [PDF]

Stat Methods Med Res
McNealis V, Moodie EE, Dean N.
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research. [PDF]

Stat Med
Salerno S, Roberts EK, Needham BL, McCormick TH, Li F, Mukherjee B, Shi X.   +6 more
europepmc   +1 more source

Smart Solar Power Site Selection Through a Hybrid Computational Framework of Neuro‐Fuzzy With Genetic Algorithm Optimization

Energy Science &Engineering, EarlyView.
Solar Power plants at various locations a: Pavagada SPP, Karnataka b: Bhadla SPP, Rajasthan c: West Bengal Solar Park ABSTRACT This paper presents a new neuro‐fuzzy multi‐criteria decision‐making (MCDM) framework designed to optimize the selection of solar power plant (SPP) sites across India.
Rajkumari Malemnganbi Devi, Benjamin A. Shimray, Ingudam Chitrasen Meitei, Khelchandra Thongam, Shuma Adhikari, Anuradha Laishram, Subir Datta, Ahmed Al Mansur, Taha Selim Ustun   +8 more
wiley   +1 more source

Assessing Treatment Effects in Observational Data With Missing Confounders: A Comparative Study of Practical Doubly-Robust and Traditional Missing Data Methods. [PDF]

Stat Med
Williamson BD, Krakauer C, Johnson E, Gruber S, Shepherd BE, van der Laan MJ, Lumley T, Lee H, Hernández-Muñoz JJ, Zhao F, Dutcher SK, Desai R, Simon GE, Shortreed SM, Nelson JC, Shaw PA.   +15 more
europepmc   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, EarlyView.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source

Evaluation of statistical methods in R for estimating intervention effects using segmented linear regression in the AB interrupted time series design. [PDF]

BMC Med Res Methodol
Pang J, Chen H, Valente MJ.
europepmc   +1 more source

Hybrid Osprey‐Salp Swarm Optimization Algorithm for Single and Multiobjective Optimal Power Flow in Smart Grids With Renewable Energy Integration

Energy Science &Engineering, EarlyView.
The proposed hybrid osprey‐salp swarm optimization algorithm addresses optimal power flow (OPF) problems in smart grids incorporating solar, hydro, and thermal generators. The algorithm is validated on Institute of Electrical and Electronics Engineers 30‐, 57‐, and 118‐bus test systems across five single and multiobjective OPF scenarios.
Mujtaba Ali, Muhammad Yaqoob Javed, Aamer Bilal Asghar, Gang Xiong, Krzysztof Ejsmont, Xiaoli Liu   +5 more
wiley   +1 more source