Results 141 to 150 of about 50,437 (269)

Effect of epileptogenesis on hypercapnic cardioventilatory response in kainic acid rats

Epilepsia, EarlyView.
Abstract Objective Cardioventilatory failure is the leading mechanism proposed to underlie sudden unexpected death in epilepsy (SUDEP), which occurs predominantly at night in patients with generalized tonic–clonic seizures. Interictal hypercapnic cardioventilatory responses are suggested to be involved, as they are ablated in chronically epileptic ...
Auriane Apaire, Elise Collard, Abigail Niyibizi, Natasha N. Kumar, Enrique Germany Morrison, Javier Chavez Cerda, Ayse S. Dereli, Riem El Tahry   +7 more
wiley   +1 more source

Machine learning and mathematical modeling for comparative analysis of green-synthesized ZnO nanoparticles as seed nano-priming agents for linseed. [PDF]

Front Plant Sci
Şavşatlı Y, Aasim M, Katırcı R, Talaz O, Altaf MT.   +4 more
europepmc   +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, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients. [PDF]

Nurs Crit Care
Guven S, Aslan FE, Canayaz M.
europepmc   +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

Development and internal validation of an interpretable machine-learning model for identifying comorbid atrial fibrillation in patients with diabetic kidney disease. [PDF]

Front Clin Diabetes Healthc
Li X, Wang X, Wang S, Zhang X.
europepmc   +1 more source

PMU‐Based Wide Area Monitoring With Machine Learning to Prevent Blackouts in Bangladesh Power System

Energy Science &Engineering, EarlyView.
A Unified Real‐time Dynamic State Measurements (URTDSM) system with PMU and Phasor Data Concentrator (PDC) deployment plan has been proposed to avoid blackout in the Bangladeshi power system. Machine learning has been used to process data from PMU to identify abnormal events. ABSTRACT The electrical power system must be trustworthy and secure enough to
Imi Bintey Fariha Rahman, Md. Minarul Islam, Md. Shahin Parvej, Abdul Hasib Chowdhury, Taha Selim Ustun, Kashem M. Muttaqi   +5 more
wiley   +1 more source

Prediction of atelectasis in <i>Mycoplasma pneumoniae</i> pneumonia using a SHapley Additive exPlanations-interpretable machine learning model. [PDF]

Front Pediatr
Sun J, Wang T, Li M, Wang M.
europepmc   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

Privacy-Aware Synthetic Tabular Data Generation for Healthcare: Application to Sepsis Detection. [PDF]

Bioengineering (Basel)
Macias-Fassio E, Morales A, Pruenza C, Fierrez J, Espósito C.   +4 more
europepmc   +1 more source