A Comparative Machine Learning Study of Connectivity-Based Biomarkers of Schizophrenia
Victoria Shevchenko,
R. Austin Benn,
Robert Scholz
et al.
Abstract:Functional connectivity holds promise as a biomarker of psychiatric disorders. Yet, its high dimensionality, combined with small sample sizes in clinical research, increases the risk of overfitting when the aim is prediction. Recently, low-dimensional representations of the connectome such as macroscale cortical gradients and gradient dispersion have been proposed, with studies noting consistent gradient and dispersion differences in psychiatric conditions. However, it is unknown which of these derived measure… Show more
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