A multiple hold-out framework for sparse partial least squares

JM Monteiro, A Rao, J Shawe-Taylor… - Journal of neuroscience …, 2016 - Elsevier
Background Supervised classification machine learning algorithms may have limitations
when studying brain diseases with heterogeneous populations, as the labels might be …

[HTML][HTML] Multiple holdouts with stability: improving the generalizability of machine learning analyses of brain–behavior relationships

A Mihalik, FS Ferreira, M Moutoussis, G Ziegler… - Biological …, 2020 - Elsevier
Abstract Background In 2009, the National Institute of Mental Health launched the Research
Domain Criteria, an attempt to move beyond diagnostic categories and ground psychiatry …

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging

MJ Rosa, MA Mehta, EM Pich, C Risterucci… - Frontiers in …, 2015 - frontiersin.org
An increasing number of neuroimaging studies are based on either combining more than
one data modality (inter-modal) or combining more than one measurement from the same …

[PDF][PDF] Técnicas de clusterização e estratificação de indivíduos para estudo de redes funcionais cerebrais

TC Ramos - 2021 - scholar.archive.org
TIMEUSPDC Page 1 Técnicas de clusterização e estrati cação de indivíduos para estudo de
redes funcionais cerebrais Taiane Coelho Ramos T IME USP DC Programa: Ciência da …

[PDF][PDF] Sparse multivariate measures of similarity between intra-modal neuroimaging datasets

MJ Rosa, MA Mehta, E Merlo Pich, C Risterucci… - 2015 - repository.ubn.ru.nl
An increasing number of neuroimaging studies are based on either combining more than
one data modality (inter-modal) or combining more than one measurement from the same …