17 citations · 33 across the 4 of their papers we have counts for
4 papers
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…
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…
Finding the needle in high-dimensional haystack: A tutorial on canonical correlation analysis
Hao-Ting Wang, Jonathan Smallwood, Janaina Mourao-Miranda +4
Since the beginning of the 21st century, the size, breadth, and granularity of data in biology and medicine has grown rapidly. In the example of neuroscience, studies with thousand…
Interpreting weight maps in terms of cognitive or clinical neuroscience: nonsense?
Jessica Schrouff, Janaina Mourao-Miranda
Since machine learning models have been applied to neuroimaging data, researchers have drawn conclusions from the derived weight maps. In particular, weight maps of classifiers bet…