Clinical AI claims face adversarial review. From regulators.
FDA expects clinical validation
SaMD submissions require evidence that goes beyond accuracy metrics. Clinical utility claims need verified support.
Benchmark gaming is everywhere
Models that perform well on standard datasets may fail in deployment. Adversarial review catches overfitting before reviewers do.
Bias claims require proof
Fairness assertions need cross-validated evidence. 'We tested on diverse populations' isn't enough for regulatory scrutiny.
Adversarial review before regulatory submission.
656-paper clinical AI corpus
Diagnostic AI, clinical decision support, SaMD validation studies. Indexed by modality and regulatory pathway.
Adversarial claim testing
Claims that survive multi-model adversarial attack are stronger submissions. Claims that don't survive save you a rejection cycle.
Citation verification
Every DOI is checked against live databases before delivery. Fabricated or mismatched references are flagged.
What the pipeline produces.
Pre-submission adversarial review: FDA reviewers apply adversarial pressure to your clinical validation claims. The question is whether you see the weaknesses first. Claims that survive multi-model attack are stronger submissions.
Research audit for clinical AI work.
Send one validation claim, clinical utility assertion, or bias analysis. We run it through cross-architecture adversarial review.