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A Multi-modal Convolutional Neural Network Framework for the Prediction of Alzheimer's Disease.

, , , , and . EMBC, page 1271-1274. IEEE, (2018)

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A realistic neuronal network and neurovascular coupling model for the study of multivariate directed connectivity in fMRI data., , , and . EMBC, page 5537-5540. IEEE, (2018)Globally conditioned causality in estimating directed brain-heart interactions through joint MRI and RR series analysis., , , , , , and . EMBC, page 3795-3798. IEEE, (2015)Estimating directed brain-brain and brain-heart connectivity through globally conditioned Granger causality approaches., , , , , and . EMBC, page 4367-4370. IEEE, (2017)Genetically dependent modulation of serotonergic inactivation in the human prefrontal cortex., , , , , , and . NeuroImage, 40 (3): 1264-1273 (2008)A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease., , , , and . NeuroImage, (2019)Dynamic inter-network connectivity in the human brain., , , , , and . EMBC, page 3313-3316. IEEE, (2017)Reconstructing multivariate causal structure between functional brain networks through a Laguerre-Volterra based Granger causality approach., , , , , and . EMBC, page 5477-5480. IEEE, (2016)A Machine Learning Tool for Interpreting Differences in Cognition Using Brain Features., , , and . AIAI, volume 559 of IFIP Advances in Information and Communication Technology, page 475-486. Springer, (2019)Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain., , , , , and . Entropy, 21 (7): 661 (2019)Resting-state brain correlates of cardiovascular complexity., , , , , , and . EMBC, page 3317-3320. IEEE, (2017)