TRIBE v2 is a multimodal AI model that predicts human brain activity more accurately than linear encoding models and recovers established neuroscientific findings through in-silico testing.
Nature methods , volume=
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A generative framework using geometric diffusion for brain networks and tabular diffusion for other organs integrates ICD-coded SDoH proxies to improve disease reasoning on UK Biobank data.
NeuroAgent uses a hierarchical LLM agent framework with Generate-Execute-Validate loops to automate neuroimaging preprocessing, reaching 84.8% end-to-end correctness and 0.9518 AUC for Alzheimer's classification on 1470 ADNI subjects using four modalities.
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A foundation model of vision, audition, and language for in-silico neuroscience
TRIBE v2 is a multimodal AI model that predicts human brain activity more accurately than linear encoding models and recovers established neuroscientific findings through in-silico testing.