5 papers
GRID: Modeling Health Influencer Discourse as Argument Networks for Credibility Assessment
Nishanth Sridhar Nakshatri, Eylon Caplan, Dan Goldwasser
Health-related discussions on social media are increasingly shaped by influencers who offer diverse, and often competing perspectives on the same issue. Yet, such content is typica…
Discovering Subtypes of Neurodegenerative Progression with a Scalable Connectome-Constrained Dynamic Model
Daniel Semchin, Emile d'Angremont, Hao Ding +6
Parkinson's disease is clinically and biologically heterogeneous, yet its spatiotemporal progression remains poorly characterized. We present a connectome-constrained disease progr…
SMART: A Flexible, Interpretable, and Scalable Spatio-temporal Brain Atlas from High-Resolution Imaging Data
John Kalkhof, Boris Gutman, Emile d'Angremont +2
We introduce SMART, a framework for learning a flexible, interpretable, and scalable spatio-temporal brain atlas from longitudinal high-resolution 3D medical images. Existing appro…
Scalable Modeling of Nonlinear Network Dynamics in Neurodegenerative Disease
Daniel Semchin, Emile d'Angremont, Marco Lorenzi +1
Mechanistic models of progressive neurodegeneration offer great potential utility for clinical use and novel treatment development. Toward this end, several connectome-informed mod…
Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling
Alessandro Viani, Boris A Gutman, Emile d'Angremont +1
Modelling the progression of Degenerative Diseases (DD) is essential for detection, prevention, and treatment, yet it remains challenging due to the heterogeneity in disease trajec…