Eeg signal processing for medical diagnosis, healthcare, and monitoring: A comprehensive review

NS Amer, SB Belhaouari - IEEE Access, 2023 - ieeexplore.ieee.org
EEG is a common and safe test that uses small electrodes to record electrical signals from
the brain. It has a broad range of applications in medical diagnosis, including diagnosis of …

Exploring new horizons in neuroscience disease detection through innovative visual signal analysis

NS Amer, SB Belhaouari - Scientific Reports, 2024 - nature.com
Brain disorders pose a substantial global health challenge, persisting as a leading cause of
mortality worldwide. Electroencephalogram (EEG) analysis is crucial for diagnosing brain …

The emergence of artificial intelligence in autism spectrum disorder research: A review of neuro imaging and behavioral applications

ID KB, DRV PM - Computer Science Review, 2025 - Elsevier
The quest to find reliable biomarkers in autism spectrum disorders (ASD) is an ongoing
endeavour to identify both underlying causes and measurable indicators of this …

Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods

C Rakshe, S Kunneth, S Sundaram… - Neural Computing and …, 2024 - Springer
Autism spectrum disorder (ASD) is a neurological condition characterized by impaired
functional connectivity (FC) networks in the brain. There are several brain networks …

Elevating recommender systems: Cutting-edge transfer learning and embedding solutions

A Fareed, S Hassan, SB Belhaouari, Z Halim - Applied Soft Computing, 2024 - Elsevier
In today's information age and connected economy, Recommender Systems (RS) plays a
vital role in managing information overload and delivering personalized suggestions to …

DML‐GNN: ASD Diagnosis Based on Dual‐Atlas Multi‐Feature Learning Graph Neural Network

S Liu, C Sun, J Li, S Wang… - International Journal of …, 2025 - Wiley Online Library
To better automate the diagnosis of autism spectrum disorder (ASD) and improve diagnostic
accuracy, a graph neural network via dual‐atlas multi‐feature learning (DML‐GNN) model …

Advancing ASD diagnostic classification with features of continuous wavelet transform of fMRIand machine learning algorithms

MB Ingle, CT Rakshe… - 2023 IEEE 5th …, 2023 - ieeexplore.ieee.org
In this study, we aimed to develop a diagnostic classification model for autism spectrum
disorder (ASD) using scalograms of functional magnetic resonance imaging (fMRI) data …

Transcranial Acoustoelectric of Functional Brain Activity Extraction based on Interet of Things

B Kumar, R Sinha, P Banerjee - 2023 4th International …, 2024 - ieeexplore.ieee.org
Understanding the mind in its normal state is gaining more and more attention. The
widespread adoption of practical brain screens, such as functional cerebral oxygenation, or …

[PDF][PDF] EEG Signal Processing for Medical Diagnosis, Healthcare, and Monitoring: A Comprehensive

NS AMER, SB BELHAOUARI - 2023 - manara.qnl.qa
ABSTRACT EEG is a common and safe test that uses small electrodes to record electrical
signals from the brain. It has a broad range of applications in medical diagnosis, including …

Advancing ASD diagnostic classification using time-frequency spectrograms of fMRI BOLD signals and machine learning

T Tikaram, U Raj, R Ratnaik, JFA Ronickom - 2024 - researchsquare.com
In this study, our goal was to develop a diagnostic framework for autism spectrum disorder
(ASD) by analyzing time-frequency spectrograms generated from BOLD signals in functional …