Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

Author:

Yoshida KosukeORCID,Shimizu Yu,Yoshimoto Junichiro,Takamura Masahiro,Okada Go,Okamoto Yasumasa,Yamawaki Shigeto,Doya Kenji

Funder

Strategic Research Program for Brain Sciences from Japan Agency for Medical Research and Development, AMED

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference51 articles.

1. Toward probabilistic diagnosis and understanding of depression based on functional MRI data analysis with logistic group LASSO;Y Shimizu;PLoS ONE,2015

2. Soft modeling by latent variables: the nonlinear iterative partial least squares approach;H Wold;Perspectives in Probability and Statistics, papers in honour of MS Bartlett,1975

3. Spatial pattern analysis of functional brain images using partial least squares;A McIntosh;NeuroImage,1996

4. Partial least squares analysis of neuroimaging data: applications and advances;AR McIntosh;NeuroImage,2004

5. Linking functional and structural brain images with multivariate network analyses: a novel application of the partial least square method;K Chen;NeuroImage,2009

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