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Cancer AI models are usually tested on data from the same hospital they were built on. A registry of independent test datasets, and a rule that every model reports performance on at least one, would show which models really work.
Most published cancer AI models lack external validation, and performance drops sharply on data from other institutions. A curated registry of held-out datasets across modalities (pathology, radiology, genomics) hosted by neutral custodians, with a submission protocol that returns performance metrics without releasing the data, would make external validation routine. Journals and regulators would require a registry validation for any clinical claim.
Shares Patient-level multimodal foundation models for treatment selection, Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI that is built but not validated or deployed.
Shares Patient-level multimodal foundation models for treatment selection, Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI that is built but not validated or deployed.
Shares Patient-level multimodal foundation models for treatment selection, Pathology & radiology foundation models, AI that is built but not validated or deployed, Digital pathology & AI.
Shares Public gold-standard datasets for validating every cancer biomarker test, Pathology & radiology foundation models, AI that is built but not validated or deployed, Digital pathology & AI.
Shares Patient-level multimodal foundation models for treatment selection, Pathology & radiology foundation models, AI that is built but not validated or deployed, Digital pathology & AI.
Shares Pathology & radiology foundation models, AI that is built but not validated or deployed, Digital pathology & AI.
Shares Pathology & radiology foundation models, AI that is built but not validated or deployed, Digital pathology & AI.
Shares Pathology & radiology foundation models, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, Digital pathology & AI.