EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.

Elif Sarisik David Popovic Daniel Keeser Adyasha Khuntia Kolja Schiltz Peter G Falkai Oliver Pogarell Nikolaos Koutsouleris

Published in: Schizophrenia bulletin (2024)

ML models can extract electrophysiological signatures of MDD and SCZ for potential clinical use. However, the impact of aging processes on diagnostic separability calls for timely application of such models, possibly in early recognition settings.

Keyphrases

machine learning
bipolar disorder
major depressive disorder
genome wide
artificial intelligence
depressive symptoms
oxidative stress
functional connectivity
big data
resting state
sleep quality
gene expression
dna methylation
risk assessment