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 …
Hierarchical structured sparse learning for schizophrenia identification
Fractional amplitude of low-frequency fluctuation (fALFF) has been widely used for resting-
state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis …
state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis …
Transfer discriminative dictionary learning with label consistency for classification of EEG signals of epilepsy
T Ni, X Gu, Y Jiang - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
EEG signal classification play an important role in recognition of epilepsy. Recently,
dictionary learning algorithms have shown the effectiveness in this field. When designing …
dictionary learning algorithms have shown the effectiveness in this field. When designing …
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 …
Improved sparse representation based robust hybrid feature extraction models with transfer and deep learning for EEG classification
SK Prabhakar, SW Lee - Expert Systems with Applications, 2022 - Elsevier
Numerous studies in the field of cognitive research is dependent on
Electroencephalography (EEG) as it apprehends the neural correspondences of various …
Electroencephalography (EEG) as it apprehends the neural correspondences of various …
Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques
Schizophrenia is a severe mental disorder that has adverse effects on the behavior of an
individual such as disorganized speech and delusions. Electroencephalography (EEG) …
individual such as disorganized speech and delusions. Electroencephalography (EEG) …
Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia
Background and objective Imaging genetics has been widely used to help diagnose and
treat mental illness, eg, schizophrenia, by combining magnetic resonance imaging of the …
treat mental illness, eg, schizophrenia, by combining magnetic resonance imaging of the …
Selection of relevant features for EEG signal classification of schizophrenic patients
M Sabeti, R Boostani, SD Katebi, GW Price - Biomedical Signal Processing …, 2007 - Elsevier
In this paper, EEG signals of 20 schizophrenic patients and 20 age-matched control
participants are analyzed with the objective of determining the more informative channels …
participants are analyzed with the objective of determining the more informative channels …
[PDF][PDF] Classification of people who suffer schizophrenia and healthy people by EEG signals using deep learning
CAT Naira, C Jos - International Journal of Advanced …, 2019 - pdfs.semanticscholar.org
More than 21 million people worldwide suffer from schizophrenia. This serious mental
disorder exposes people to stigmatization, discrimination, and violation of their human …
disorder exposes people to stigmatization, discrimination, and violation of their human …
A novel approach to schizophrenia Detection: Optimized preprocessing and deep learning analysis of multichannel EEG data
S Srinivasan, SD Johnson - Expert Systems with Applications, 2024 - Elsevier
Schizophrenia diagnosis, characterized by cognitive deficits, hallucinations, and delusions,
poses challenges due to its complex nature. Electroencephalogram (EEG) signals provide …
poses challenges due to its complex nature. Electroencephalogram (EEG) signals provide …
相关搜索
- schizophrenia classification mobile healthcare
- schizophrenia classification dictionary learning
- mobile healthcare dictionary learning
- eeg classification deep learning
- sparse autoencoder classification of schizophrenia
- learning analysis schizophrenia detection
- eeg signals schizophrenia detection
- eeg signals discriminative dictionary
- classification of people eeg signals
- eeg signals machine learning
- schizophrenia classification deep learning
- schizophrenia classification machine learning
- eeg signals deep learning
- classification of people deep learning
- machine learning schizophrenia detection