Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
A pyramidal spatial-based feature attention network for schizophrenia detection using electroencephalography signals
Automatic signal classification is utilized in various medical and industrial applications,
particularly in schizophrenia (SZ) diagnosis, one of the most prevalent chronic neurological …
particularly in schizophrenia (SZ) diagnosis, one of the most prevalent chronic neurological …
[HTML][HTML] 3D convolutional neural network for schizophrenia detection using as EEG-based functional brain network
M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2024 - Elsevier
Schizophrenia (ScZ) is a chronic mental disorder affecting the function of the brain, which
causes emotional, social, and cognitive problems. This paper explored the functional brain …
causes emotional, social, and cognitive problems. This paper explored the functional brain …
EEG-based schizophrenia classification using penalized sequential dictionary learning in the context of mobile healthcare
Mobile healthcare is an appealing approach based on the Internet of Medical Things (IoMT)
and cloud computing. It can lead to unobstructed, economical, and patient-centric healthcare …
and cloud computing. It can lead to unobstructed, economical, and patient-centric healthcare …
[HTML][HTML] Chaotic marine predator optimization algorithm for feature selection in schizophrenia classification using EEG signals
Schizophrenia is a chronic mental illness that can negatively affect emotions, thoughts,
social interaction, motor behavior, attention, and perception. Early diagnosis is still …
social interaction, motor behavior, attention, and perception. Early diagnosis is still …
Brain–Computer Interface Based on PLV-Spatial Filter and LSTM Classification for Intuitive Control of Avatars
This study researches the combination of the brain–computer interface (BCI) and virtual
reality (VR) in order to improve user experience and facilitate control learning in a safe …
reality (VR) in order to improve user experience and facilitate control learning in a safe …
Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals
Numerous studies on early detection of schizophrenia (SZ) have utilized all available
channels or employed set of a few time domain or frequency domain features, while a …
channels or employed set of a few time domain or frequency domain features, while a …
Single-Channel EEG Data Analysis Using a Multi-Branch CNN for Neonatal Sleep Staging
HA Siddiqa, Z Tang, Y Xu, L Wang, M Irfan… - IEEE …, 2024 - ieeexplore.ieee.org
Neonatal sleep staging is crucial for understanding infant brain development and assessing
neurological health. This study explores the optimal electrode configuration to reduce …
neurological health. This study explores the optimal electrode configuration to reduce …
Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images
Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long
time. In fact, individuals with SZ experience a blurred line between fantasy and reality …
time. In fact, individuals with SZ experience a blurred line between fantasy and reality …
Application of continuous wavelet transform and support vector machine for autism spectrum disorder electroencephalography signal classification
The article's subject matter is to classify Electroencephalography (EEG) signals in Autism
Spectrum Disorder (ASD) sufferers. The goal is to develop a classification model using …
Spectrum Disorder (ASD) sufferers. The goal is to develop a classification model using …