Machine learning techniques to improve the value of neurophysiological measurements for individual patients

The main topic in this PhD thesis was applying machine learning techniques in neurological disorders, in order to individually distinguish patients from healthy controls, patients with different diseases or patients with different disease severity. This thesis is intended to recapitulate a PhD in which a broad range of subjects was covered. To start with, three different diseases were investigated: schizophrenia, dementia and multiple sclerosis. Two different measurement techniques were used in these studies: electroencephalography and magnetoencephalography. Finally, different analysis methods were applied, such as peak extraction, frequency spectrum analysis, network analysis, group difference analysis and classification.

Jaar van publicatie:2017

Trefwoorden:dementia