Machine learning approaches and non-linear processing of extracted components in frontal region to predict rTMS treatment response in major depressive disorder

Predicting the therapeutic result of repetitive transcranial magnetic stimulation (rTMS) treatment could save time and costs as ineffective treatment can be avoided. To this end, we presented a machine-learning-based strategy for classifying patients with major depression disorder (MDD) into respond...

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Detalhes bibliográficos

Principais autores:	Elias Ebrahimzadeh, Farahnaz Fayaz, Lila Rajabion, Masoud Seraji, Fatemeh Aflaki, Ahmad Hammoud, Zahra Taghizadeh, Mostafa Asgarinejad, Hamid Soltanian-Zadeh
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2023-03-01
Colecção:	Frontiers in Systems Neuroscience
Assuntos:	electroencephalography (EEG) repetitive transcranial magnetic stimulation (rTMS) major depressive disorder (MDD) prediction treatment response independent component analysis (ICA) classification
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fnsys.2023.919977/full
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