Results 151 to 160 of about 31,077 (302)
Biomass‐derived hydrochars as eco‐friendly adsorbents for wastewater treatment applications
Environmental Progress &Sustainable Energy, EarlyView.Abstract Emerging organic pollutants (EOPs), such as diethyl phthalate (DEP), bisphenol A (BPA), and methylene blue (MB), are only partially removed in conventional wastewater treatment plants. This study assesses hydrochars produced by hydrothermal carbonization (HTC) of spruce bark (SB), vine shoots (VSs), and wheat straw (WSs) for removing three ...
Emanuel Gheorghita Armanu +6 more
wiley +1 more source
Epileptic Disorders, EarlyView.Abstract Objective Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS remains challenging. We aimed to evaluate the prognostic potential of machine learning (ML) algorithms applied to post‐febrile seizure electroencephalography (EEG) recordings.
Boran Şekeroğlu +7 more
wiley +1 more source
Epilepsia, EarlyView.Abstract Epilepsy affects more than 50 million individuals globally and has a substantial genetic component that remains to be completely understood. Traditional studies have focused on severe, early onset cases enrolled through clinical or research settings.
Jessica Castrillon Lal +5 more
wiley +1 more source
Epilepsia, EarlyView.Abstract Objective Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first‐line ASM, yet only approximately half of patients achieve sustained seizure freedom. Treatment selection remains largely empirical.
Simeon Platte +15 more
wiley +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Epilepsia Open, EarlyView.Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Equine Veterinary Journal, EarlyView.Abstract Background Racehorses undergo profound physiological changes with training and competition, but current biomarkers inadequately capture the complex molecular dynamics of exercise. This study aimed to identify novel plasma biomarkers of training adaptation and peak load using high‐throughput proteomics.
Jowita Grzędzicka +4 more
wiley +1 more source
Best-first search-based approach for mining top-k closed frequent itemsets from uncertain databases. [PDF]
PLoS OneLe N, Vo H, Nguyen T.
europepmc +1 more source
Photodynamic Biomimetic Nanoparticles Accelerate Tumor Vascular Normalization Initiation
Exploration, EarlyView.Platelet‐mimetic IA@PM integrates apatinib‐driven vascular normalization with ICG‐mediated photodynamic therapy, creating a self‐amplifying vascular normalization therapy (VNT)–photodynamic therapy (PDT) cycle that accelerates the onset of the vascular normalization window and potentiates antitumor treatment.
Yufei Liu +6 more
wiley +1 more source
Detection of Interpretable and Fine-Grained Brain Tumor Magnetic Resonance Imaging Based on Progressive Pruning: Machine Learning Model Development and Validation Study. [PDF]
JMIR Med InformLiu Y, Song S, Lian S, Zhang X.
europepmc +1 more source
Preserving the essential features in CNNs: pruning and analysis
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024The exceptional performance of Convolutional Neural Networks (CNNs) entails increasing requirements in computing power and storage.
López González, Clara Isabel +3 more
core +1 more source