An SVD-based method for DBS artifact removal: High-fidelity restoration of local field potential DOI
Long Chen, Z. Z. Ren, Jing Wang

et al.

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 108, P. 107908 - 107908

Published: May 2, 2025

Language: Английский

Integrating chemical artificial intelligence and cognitive computing for predictive analysis of biological pathways: a case for intrinsically disordered proteins DOI
Orkid Coskuner‐Weber, Pier Luigi Gentili, Vladimir N. Uversky

et al.

Biophysical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 15, 2025

Language: Английский

Citations

0
A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry DOI

Jaleh Bagheri Hamzyan Olia,

Arasu Raman, Chou‐Yi Hsu

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 189, P. 109984 - 109984

Published: March 14, 2025

Language: Английский

Citations

0
Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images DOI Creative Commons
Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 10, 2025

Language: Английский

Citations

0
The neuroplastic brain: current breakthroughs and emerging frontiers DOI Creative Commons
Parisa Gazerani

Brain Research, Journal Year: 2025, Volume and Issue: unknown, P. 149643 - 149643

Published: April 1, 2025

Language: Английский

Citations

0
Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models DOI Creative Commons

M.A. Ogundero,

Taiwo Adelakin,

Kehinde Orolu

et al.

ABUAD Journal of Engineering Research and Development (AJERD), Journal Year: 2025, Volume and Issue: 8(1), P. 292 - 306

Published: April 24, 2025

Sand production is one of the major challenges in oil and gas industry, impacting operational integrity economic efficiency extraction activities. This study focuses on predicting Reservoir Flow Capacity (RFC) sandstone formations by analyzing geological petrophysical properties critical to reservoir performance mechanical stability. It also identified key factors that impact stability during production. Given a large number input variables enclose environmental factors, set correlation these conditions provide profound analysis reveal patterns within data. With following supervised machine learning algorithms: Random Forest, Artificial Neural Network (ANN) Support Vector Regression (SVR); modeled RFC. The algorithms were selected for their ability model complex relationships characterization, with Forest excelling high-dimensional data handling, ANN pattern learning, SVR regression-based predictions. Model evaluation using R-Squared metrics showed possesses good level accuracy 0.9573 RFC, compared which had values 0.9390 0.7294 respectively. variations from actual hence was not very useful our Further developed models revealed formation thickness, permeability are most parameters influencing flow capacity overall rock

Language: Английский

Citations

0
Integrating Brain-Inspired Computation with Big-Data Analytics for Advanced Diagnostics in Neuroradiology DOI Creative Commons

A. V. Senthil Kumar,

J Ramprasath,

V. Kalpana

et al.

Neuroscience Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 100202 - 100202

Published: April 1, 2025

Language: Английский

Citations

0
Predicting Intracranial Hypertension in Traumatic Brain Injury Using AI: A Systematic Review of Algorithms and Their Clinical Integration Potential DOI Open Access

Marwa Mohamed Ahmed Elkhidir Babikir,

Faiza Ibrahim,

Haram Hafiz Osman Elhassan

et al.

Cureus, Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

Language: Английский

Citations

0
An SVD-based method for DBS artifact removal: High-fidelity restoration of local field potential DOI
Long Chen, Z. Z. Ren, Jing Wang

et al.

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 108, P. 107908 - 107908

Published: May 2, 2025

Language: Английский

Citations

0