Research projects
The group is involved in the following projects:
Pattern Recognition for Neuroimaging Toolbox (PRoNTo)
- PRoNTo is a toolbox based on machine learning techniques for the analysis of neuroimaging data. The development of the toolbox has been supported by the PASCAL Harvest framework.
Previous projects
- Selecting stable features for multivariate mapping in neuroimaging (Dr Jane Rondina)
- Predicting clinical scores from functional neuroimaging scans (Dr Liana Portugal)
- Sparse network-based discriminative models (Dr Maria Joao Rosa)
- Selection of relevant fMRI voxels using sparse CCA and rich stimulus features (Kristian Nybo)
- Prediction of disease status and the course of illness in schizophrenia patients using structural MRI brain pattern classification (Mireille Nieuwenhuis)
- Elastic-net Multiple Kernel Learning for multi-region neuroimaging-based diagnosis (Dr Janaina Mourao-Miranda)