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Kernel methods for fMRI pattern prediction., , , and . IJCNN, page 692-697. IEEE, (2008)Utilizing temporal information in fMRI decoding: Classifier using kernel regression methods., , , , , and . NeuroImage, 58 (2): 560-571 (2011)Kernel regression for fMRI pattern prediction., , , , and . NeuroImage, 56 (2): 662-673 (2011)PRoNTo: Pattern Recognition for Neuroimaging Toolbox., , , , , , , , and . Neuroinformatics, 11 (3): 319-337 (2013)Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes., , , , , and . NeuroImage, 49 (3): 2178-2189 (2010)Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images., , , , and . NeuroImage, 60 (1): 59-70 (2012)Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy., , , , , , , , , and 13 other author(s). CoRR, (2018)Effects of image contrast on functional MRI image registration., , , , , and . NeuroImage, (2013)Predicting clinical scores from magnetic resonance scans in Alzheimer's disease., , , , , and . NeuroImage, 51 (4): 1405-1413 (2010)Face-selective regions differ in their ability to classify facial expressions., , , , , and . NeuroImage, (2016)