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Once an AI tool is in use, its maker and the hospital would have to report regularly how it is actually performing on real patients, and the reports would be public.
Post-market surveillance of medical devices focuses on adverse events, not performance. For AI, the relevant harm is silent degradation. The proposal requires deployed cancer AI to report standardised performance metrics (sensitivity, specificity, calibration, subgroup results, override rates) per site quarterly to the model registry, with thresholds that trigger regulator review, analogous to pharmacovigilance periodic safety update reports.
Shares A public registry of every AI model used in cancer care, A standard for monitoring AI performance drift with pause thresholds, 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 A public registry of every AI model used in cancer care, 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 A standard for monitoring AI performance drift with pause thresholds, 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 A public registry of every AI model used in cancer care, 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.