activity
20192024
most citedIdentifying latent disease factors differently expressed in patient subgroups using group factor analysis

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

stat.ML2024★ 1 cited

Identifying latent disease factors differently expressed in patient subgroups using group factor analysis

Fabio S. Ferreira, John Ashburner, Arabella Bouzigues +33

In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and…

stat.ML2021

A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets

Fabio S. Ferreira, Agoston Mihalik, Rick A. Adams +2

Canonical Correlation Analysis (CCA) and its regularised versions have been widely used in the neuroimaging community to uncover multivariate associations between two data modaliti…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

Neil P. Oxtoby, Fabio S. Ferreira, Agoston Mihalik +12

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions acr…

q-bio.NC2019

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

Agoston Mihalik, Mikael Brudfors, Maria Robu +12

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABC…