SchizoGoogLeNet: The GoogLeNet‐Based Deep Feature Extraction Design for Automatic Detection of Schizophrenia
Schizophrenia (SZ) is a severe and prolonged disorder of the human brain where people
interpret reality in an abnormal way. Traditional methods of SZ detection are based on …
interpret reality in an abnormal way. Traditional methods of SZ detection are based on …
1D-convolutional neural network approach and feature extraction methods for automatic detection of schizophrenia
H Göker - Signal, Image and Video Processing, 2023 - Springer
Schizophrenia is a complex psychiatric disorder characterized by delusions, hallucinations,
disorganized speech, mood disturbances, and abnormal behavior. Early diagnosis of …
disorganized speech, mood disturbances, and abnormal behavior. Early diagnosis of …
[引用][C] Bridging the Gap: Deep Learning EEG-based Applications for Schizophrenia Classification and Management
A systematic review of EEG based automated schizophrenia classification through machine learning and deep learning
The electroencephalogram (EEG) serves as an essential tool in exploring brain activity and
holds particular importance in the field of mental health research. This review paper …
holds particular importance in the field of mental health research. This review paper …
Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
The complexity and heterogeneity of schizophrenia symptoms challenge an objective
diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the …
diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the …
Fusion of pattern-based and statistical features for Schizophrenia detection from EEG signals
Schizophrenia (SZ) is a chronic disorder affecting the functioning of the brain. It can lead to
irrational behaviour amongst the patients suffering from this disease. A low-cost diagnostic …
irrational behaviour amongst the patients suffering from this disease. A low-cost diagnostic …
The EEG multiverse of schizophrenia
JR da Cruz, D Gordillo, E Chkonia, WH Lin, O Favrod… - medRxiv, 2020 - medrxiv.org
Research on schizophrenia typically focuses on one paradigm, for which clear-cut
abnormalities between patients and controls are established. Great care is taken to …
abnormalities between patients and controls are established. Great care is taken to …
A Novel Brain Connectivity-Powered Graph Signal Processing Approach for Automated Detection of Schizophrenia from Electroencephalogram Signals
Schizophrenia is a severe neural disorder that affects around 24 million individuals globally.
In this context, Electroencephalogram (EEG) signal-based analysis and automated …
In this context, Electroencephalogram (EEG) signal-based analysis and automated …
Automated diagnosis of schizophrenia based on spatial–temporal residual graph convolutional network
X Xu, G Zhu, B Li, P Lin, X Li, Z Wang - BioMedical Engineering OnLine, 2024 - Springer
Background Schizophrenia (SZ), a psychiatric disorder for which there is no precise
diagnosis, has had a serious impact on the quality of human life and social activities for …
diagnosis, has had a serious impact on the quality of human life and social activities for …
SzHNN: a novel and scalable deep convolution hybrid neural network framework for schizophrenia detection using multichannel EEG
In the field of neuroscience, brain activity measurement and analysis are considered crucial
areas. Schizophrenia (Sz) is a brain disorder that severely affects the thinking, behavior, and …
areas. Schizophrenia (Sz) is a brain disorder that severely affects the thinking, behavior, and …