Dementia is a clinical syndrome with several underlying causes — Alzheimer’s pathology, vascular damage, and others — which is precisely what makes it hard to predict. Several CNS projects target the transition point: identifying who will progress from mild cognitive impairment to dementia, and which biological pathways drive that progression.
CNS Projects¶
Josh Neudorf — graph neural network deep learning to predict progression from mild cognitive impairment to dementia from brain network configuration
Mohamed Abdelhack — how cardiovascular illness may predispose individuals to dementia at the level of brain function
Sima Abbasi Habashi — genetic and immune pathways driving white matter hyperintensity burden, a strong predictor of dementia
Tom George — foundation models fine-tuned on clinical tasks with a focus on dementia prediction
Trishna Saha Detroja — the bidirectional relationship between sleep and dementia at the cellular level
Lindsay Munroe — predicting progression of neurodegenerative disease with explainable AI
Related Resources¶
Datasets — ADNI, PREVENT-AD, UK Biobank
Modalities — fMRI, structural MRI, DWI
Methods — deep learning, graph neural networks
Related topics — Alzheimer’s Disease, Aging and Cognitive Decline