27 citations · 181 across the 39 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease
Alex Fedorov, Tristan Sylvain, Eloy Geenjaar +7
Sensory input from multiple sources is crucial for robust and coherent human perception. Different sources contribute complementary explanatory factors. Similarly, research studies…
On self-supervised multi-modal representation learning: An application to Alzheimer's disease
Alex Fedorov, Lei Wu, Tristan Sylvain +5
Introspection of deep supervised predictive models trained on functional and structural brain imaging may uncover novel markers of Alzheimer's disease (AD). However, supervised tra…
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov +4
Behavioral changes are the earliest signs of a mental disorder, but arguably, the dynamics of brain function gets affected even earlier. Subsequently, spatio-temporal structure of…
Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia
Haleh Falakshahi, Victor M. Vergara, Jingyu Liu +13
Objective: Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on…