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Pay independent experts to try to break cancer AI tools with unusual images, rare cases, bad scans and data shifts, and publish what breaks them.
Robustness of medical AI to artefacts, rare presentations, adversarial inputs and distribution shift is poorly characterised. The proposal funds standing red teams (imaging physicists, pathologists, security researchers) that stress-test cleared and pre-clearance cancer AI with curated adversarial and edge-case corpora, publish failure modes in a common taxonomy, and feed results to the registry and developers, as is done for cybersecurity and increasingly for general-purpose AI.
Shares Sequestered, prospectively collected benchmark datasets that no one can train on, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares Sequestered, prospectively collected benchmark datasets that no one can train on, How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.
Shares How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals, AI that is built but not validated or deployed.