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Forty-Nine Thousand Brains Built a Reusable Starting Point
GenFAR trained a general MRI representation across eleven cohorts and seventeen tasks, then transferred it to new prediction problems.
Summary
GenFAR trained a general MRI representation across eleven cohorts and seventeen tasks, then transferred it to new prediction problems.
The framework trained on MRIs from 49,246 people across 11 cohorts, using 17 tasks spanning cognition, diagnosis, demographics and biomarkers. An analysis of 5,000 task orderings selected six-task sequences and identified five strong donor tasks, including age and cognitive measures. The resulting representation improved accuracy and sample efficiency on secondary tasks not included in the original sequence. These are retrospective modeling results, not a clinical diagnostic system or evidence that one representation fits every population.
Why it matters
GenFAR trained a general MRI representation across eleven cohorts and seventeen tasks, then transferred it to new prediction problems.
Limits and context
- The resulting representation improved accuracy and sample efficiency on secondary tasks not included in the original sequence.
- These are retrospective modeling results, not a clinical diagnostic system or evidence that one representation fits every population.
Key claims
GenFAR trained a general MRI representation across eleven cohorts and seventeen tasks, then transferred it to new prediction problems.
Qualification: The resulting representation improved accuracy and sample efficiency on secondary tasks not included in the original sequence.
Evidence: source-2026-08-13-010
Sources
- arXiv preprint 2608.12185arXiv · primary research
Corrections
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