Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features
Recently, an increasing number of researchers have endeavored to develop practical tools
for diagnosing patients with schizophrenia using machine learning techniques applied to …
for diagnosing patients with schizophrenia using machine learning techniques applied to …
Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network
M Shen, P Wen, B Song, Y Li - Computers in Biology and Medicine, 2023 - Elsevier
Schizophrenia (ScZ) is a devastating mental disorder of the human brain that causes a
serious impact of emotional inclinations, quality of personal and social life and healthcare …
serious impact of emotional inclinations, quality of personal and social life and healthcare …
Development of a machine learning based algorithm to accurately detect schizophrenia based on one-minute EEG recordings
R Buettner, D Beil, S Scholtz, A Djemai - 2020 - scholarspace.manoa.hawaii.edu
While diagnosing schizophrenia by physicians based on patients' history and their overall
mental health is inaccurate, we report on promising results using a novel, fast and reliable …
mental health is inaccurate, we report on promising results using a novel, fast and reliable …
An interpretable machine learning method for the detection of schizophrenia using EEG signals
In this work we propose a machine learning (ML) method to aid in the diagnosis of
schizophrenia using electroencephalograms (EEGs) as input data. The computational …
schizophrenia using electroencephalograms (EEGs) as input data. The computational …
Deep convolutional neural network model for automated diagnosis of schizophrenia using EEG signals
A computerized detection system for the diagnosis of Schizophrenia (SZ) using a
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
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 …
Exploring deep residual network based features for automatic schizophrenia detection from EEG
Schizophrenia is a severe mental illness which can cause lifelong disability. Most recent
studies on the Electroencephalogram (EEG)-based diagnosis of schizophrenia rely on …
studies on the Electroencephalogram (EEG)-based diagnosis of schizophrenia rely on …
EEG microstate features for schizophrenia classification
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG
activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four …
activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four …
From sound perception to automatic detection of schizophrenia: an EEG-based deep learning approach
Deep learning techniques have been applied to electroencephalogram (EEG) signals, with
promising applications in the field of psychiatry. Schizophrenia is one of the most disabling …
promising applications in the field of psychiatry. Schizophrenia is one of the most disabling …
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) …