Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023

M Jafari, D Sadeghi, A Shoeibi, H Alinejad-Rokny… - Applied …, 2024 - Springer
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …

Neural Correlate-Based E-Learning Validation and Classification Using Convolutional and Long Short-Term Memory Networks.

D Pathak, R Kashyap - Traitement du Signal, 2023 - search.ebscohost.com
The COVID-19 pandemic has precipitated an unprecedented surge in the proliferation of
online E-learning platforms, designed to cater to a wide array of subjects across all age …

Bridging the Gap Between Modalities with Cross-Modal Generative AI and Large Model

AP Srivastava, P Gupta, VH Raj… - 2024 IEEE 13th …, 2024 - ieeexplore.ieee.org
The Multi-Modal Cross-Attention Network (MCAN) is a revolutionary way to bridge the gap
between varied data modalities that has emerged in response to the growing field of cross …

[HTML][HTML] Multi-channel delineation of intracardiac electrograms for arrhythmia substrate analysis using implicitly regularized convolutional neural network with wide …

J Hejc, R Redina, J Kolarova, Z Starek - Biomedical Signal Processing and …, 2024 - Elsevier
Objective Automated segmentation of intracardiac electrograms and extraction of
fundamental cycle length intervals is crucial for reproducible arrhythmia substrate analysis …

[HTML][HTML] Improved Dipole Source Localization from Simultaneous MEG-EEG Data by Combining a Global Optimization Algorithm with a Local Parameter Search: A …

S Bastola, S Jahromi, R Chikara, SM Stufflebeam… - Bioengineering, 2024 - mdpi.com
Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently
constitutes an optimization problem aimed at solving the inverse problem of electric current …

Low-frequency motor cortex EEG predicts four rates of force development

R O'Keeffe, SY Shirazi, A Del Vecchio… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The movement-related cortical potential (MRCP) is a low-frequency component of the
electroencephalography (EEG) signal that originates from the motor cortex and surrounding …

Automatic detection and interpretable analysis of learners' cognitive states based on electroencephalogram signals

Y Li, X He, P Wang, J Fang, Y Li, Y Li - Thinking Skills and Creativity, 2024 - Elsevier
The development of higher-order thinking skills (HOTS) in learners is one of the educational
objectives of the 21st century. Detecting learners' higher and lower cognitive states based …

The potential of industrial smart grids in optimizing energy consumption

HS Shreenidhi, S Upadhyay… - 2024 IEEE 13th …, 2024 - ieeexplore.ieee.org
In order to maximize the benefits of industrial smart grids in terms of energy optimization, this
research presents the Dynamic Energy Optimization System for Industrial Smart Grids …

Advanced AI approaches for detailed examination of individuals prone to nightly respiratory challenges using medical records

DK Srivastava, S Parveen… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The advancement of Artificial Intelligence (AI) has opened new avenues for the detailed
examination of individuals prone to nightly respiratory challenges using medical records …

The Role of Cognitive Radio in Optimizing Spectrum Utilization

ALN Rao, B Ramesh, A Jain… - 2024 IEEE 13th …, 2024 - ieeexplore.ieee.org
Spectrum optimization is a key objective in wireless communication as data-intensive
services proliferate. Cognitive radio technology, which handles airwaves smartly and …