Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features

@article{Shim2016MachinelearningbasedDO,
  title={Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features},
  author={M. Shim and Han-Jeong Hwang and D. Kim and S. Lee and C. Im},
  journal={Schizophrenia Research},
  year={2016},
  volume={176},
  pages={314-319}
}
Recently, an increasing number of researchers have endeavored to develop practical tools for diagnosing patients with schizophrenia using machine learning techniques applied to EEG biomarkers. Although a number of studies showed that source-level EEG features can potentially be applied to the differential diagnosis of schizophrenia, most studies have used only sensor-level EEG features such as ERP peak amplitude and power spectrum for machine learning-based diagnosis of schizophrenia. In this… Expand
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