Recent advances in electroencephalogram (EEG) signal classification have primarily
focused on domain-specific approaches, which impede algorithm cross-discipline capability …

Using phase space reconstruct technique from one-dimensional and multi-dimensional time
series and the quantitative criterion rule of system chaos, and combining the neural network; …

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions,
and disordered thinking. Traditionally, SCZ diagnosis involves the subject's interview by a …

We aimed to develop a machine learning (ML) classifier to detect and compare major
psychiatric disorders using electroencephalography (EEG). We retrospectively collected …

The complex, nonlinear and non-stationary electroencephalogram (EEG) signals are very
tedious to interpret visually and highly difficult to extract the significant features from them …

Normal life can be ensured for schizophrenic patients if diagnosed early.
Electroencephalogram (EEG) carries information about the brain network connectivity which …

Schizophrenia (SCZ) is a severe neurological and physiological syndrome that perverts a
patient's perception of reality. SCZ exhibits several symptoms, including hallucinations …

Schizophrenia (SZ) is categorized as positive SZ and negative SZ in terms of the
predominant symptom. In this study, we proposed the hypothesis that positive SZ had more …

Quasi-stable electrical fields in the EEG, called microstates carry information on the
dynamics of large scale brain networks. Using machine learning techniques, we explored …

Structural changes in the hippocampus and amygdala have been demonstrated in
schizophrenia patients. However, whether morphological information from these subcortical …