1. Abdulkadir, A., Peter, J., Ronneberger, O., Brox, T., & Klöppel, S. (2014). Voxel-based multi-class classification of AD, MCI, and elderly controls. In Medical image computing and computer-assisted intervention (MICCAI) 2014-CADDementia Challenge.
2. Bellec, P., Chu, C., Chouinard-Decorte, F., Benhajali, Y., Margulies, D.S., & Craddock, R.C. (2017). The neuro bureau ADHD-200 preprocessed repository. NeuroImage, 144, 275–286.
3. Bi, J., Bennett, K., Embrechts, M., Breneman, C., & Song, M. (2003). Dimensionality reduction via sparse support vector machines. Journal of Machine Learning Research, 3(Mar), 1229–1243.
4. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.
5. Bron, E.E., Smits, M., Van Der Flier, W.M., Vrenken, H., Barkhof, F., Scheltens, P., Papma, J.M., Steketee, R.M., Orellana, C.M., Meijboom, R., & et al. (2015). Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge. NeuroImage, 111, 562–579.