Every AI output logged in the record with input hash, version and clinician response
Whenever an AI tool gives a result about a patient, the hospital system would permanently record what it saw, which version it was, what it said and what the doctor did with it.
Most AI outputs are transient and not stored, making retrospective audit, harm investigation and performance measurement impossible. The proposal is a standard for AI audit trails in the EHR (FHIR resources capturing model identifier and version, input references and hashes, output, confidence, timestamp, and the clinician's acceptance or override), required for all deployed cancer AI and feeding post-market performance reporting.
- AI that is built but not validated or deployed · Thousands of cancer AI models are published; a handful are in clinical use, and fewer have shown they help patients.
- Data silos · Records, scans, genomes and outcomes sit in separate systems that cannot talk. Every patient's experience is lost to the next.
Pages like this
not linked directly; found by shared links- IdeaA standard for monitoring AI performance drift with pause thresholds
Shares Mandatory post-market performance reporting for cancer AI, AI that is built but not validated or deployed.
- IdeaA public registry of every AI model used in cancer care
Shares Mandatory post-market performance reporting for cancer AI, AI that is built but not validated or deployed.
- IdeaOne certified open-source de-identification pipeline for scans and slides
Shares AI that is built but not validated or deployed, Data silos.
- IdeaDigitise the nation's pathology slides and link them to outcomes
Shares AI that is built but not validated or deployed, Data silos.
- IdeaFederated training of pathology and radiology models across hospitals
Shares AI that is built but not validated or deployed, Data silos.
- IdeaA federated learning consortium of cancer centres that jointly own the models
Shares AI that is built but not validated or deployed, Data silos.
- IdeaA pre-competitive consortium to train a shared multimodal cancer foundation model
Shares AI that is built but not validated or deployed, Data silos.
- IdeaPool every immunotherapy trial's biomarker data into one commons
Shares AI that is built but not validated or deployed, Data silos.