Unlike other AI models, BrainIAC needs limited data to ID key neurological health indicators A new AI foundation model has been developed that can accurately extract multiple disease risk signals from routine brain MRIs, including: estimating a person's "brain age"; predicting dementia risk; detecting brain tumor mutations; and predicting survival from brain cancer, according to investigators from Harvard-affiliated Mass General Brigham.

New research suggests that simplifying how brain imaging data are analyzed could make functional MRI scans far better at predicting individual health outcomes, a counterargument to the "just in case" MRI.

Deep within the realm of neuroscience, a revolutionary technology has been unraveling the intricacies of the human brain: functional magnetic resonance imaging (fMRI).