ArticleImaging neuroscience (Cambridge, Mass.)2024
Classification accuracy of structural and functional connectomes across different depressive phenotypes.
Article in Imaging neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Phenotyping of major depressive disorder (MDD) can vary from study to study, which, together with heterogeneity of the disorder, may contribute to the inconsistent associations with neuroimaging features and underlie previous problems with machine-learning methods for MDD diagnostic applications. In this study, we examined the classification accuracy of structural and functional connectomes across different depressive phenotypes, including separating MDD subgroups into those with and without self-reported exposure to childhood trauma (CT) (one of the largest risk factors for MDD associated with brain development). We applied logistic ridge regression to classify control and MDD participants defined by six different MDD definitions in a large community-based sample (
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