Schizo-Net: A novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices

N Grover, A Chharia, R Upadhyay… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions,
and disordered thinking. Traditionally, SCZ diagnosis involves the subject's interview by a …

An Effective Detection and Classification of Schizophrenia Patients from Eeg Signals Using Machine Learning Algorithms

P Sekar - papers.ssrn.com
A brain condition called schizophrenia has a significant impact on people's thinking,
behaviors, and lives on a global state. The prevalence of the condition rises along with the …

Automated detection of schizophrenia using deep learning: a review for the last decade

M Sharma, RK Patel, A Garg, R SanTan… - Physiological …, 2023 - iopscience.iop.org
Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like
thought, perception, etc., with a profound impact on the individual's life. Deep learning (DL) …

[PDF][PDF] Multi-class EEG signal classification with statistical binary pattern synergic network for schizophrenia severity diagnosis.

PE Rani, B Pavan - AIMS Biophysics, 2023 - aimspress.com
Multi-class EEG signal classification with statistical binary pattern synergic network for
schizophrenia severity diagnosis Page 1 AIMS Biophysics, 10(3): 347–371. DOI: 10.3934/biophy.2023021 …

Recognition of Schizophrenia Patients by EEG Signal Using the STFT/CWT Layer with Group-Convolution

VQ Huynh, H Do Tran… - 2023 RIVF International …, 2023 - ieeexplore.ieee.org
The classic method of diagnosing schizophrenia involves a qualified psychiatrist
interviewing the patient. Furthermore, a severe psychological condition significantly harms …

Deep Learning with EEG Data

B Tekeste - 2023 - oda.oslomet.no
Electroencephalogram (EEG) data has shown great promise but requires sophisticated
methods due to the complex spatial and temporal patterns found in such data, so this …

Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques

F Hassan, SF Hussain, SM Qaisar - Information Fusion, 2023 - Elsevier
Schizophrenia is a severe mental disorder that has adverse effects on the behavior of an
individual such as disorganized speech and delusions. Electroencephalography (EEG) …

Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images

M Mostafavi, SB Ko, SB Shokouhi… - Physical and Engineering …, 2024 - Springer
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 …

Leveraging EEG Signals and Machine Learning for Schizophrenia Classification

A Elfarsy, S El-Metwally - 2024 6th International Conference on …, 2024 - ieeexplore.ieee.org
Schizophrenia is a neurological disorder known for its potential to disrupt brain function and
cause erratic behavior. Timely diagnosis and intervention are crucial for improving patient …

A modified convolutional neural network for resting-state EEG-based schizophrenia classification with weighted electrodes

D Ma, G Yang, Z Li, H Liu, C Pan, L Li… - Journal of Medical …, 2020 - ingentaconnect.com
Schizophrenia is a severe mental disorder that can result in hallucinations, delusions, and
extremely disordered thinking and behavior. While electroencephalography (EEG) has been …