A Deployment Audit of Release-Side Risk in Conformal Triage under Prevalence Shift

Abstract:Conformal triage converts predictive scores into deployment actions that either release a case, flag it for urgent attention, or defer it to human review. Under an observed change in target-event prevalence, however, marginal coverage and human-review rate can miss whether patients who experience the target event are released without review. To address this gap, we introduce a leakage-aware deployment audit for release-side conformal triage. It first assigns target subjects to three non-overlapping roles: prevalence correction, conformal calibration, and held-out release-side evaluation. This separation then lets the audit evaluate release directly: how many event-positive patients are cleared without review, whether the pilot has enough event labels for calibration, and how the release-review trade-off shifts. Applying this audit to a retrospective non-small-cell lung cancer (NSCLC) target cohort shows why lower review can be misleading: after prevalence correction, the pooled conformal branch lowers review by releasing more patients, some of whom are event-positive. Within the audit, the classwise branch acts as a scarcity diagnostic: the pilot has too few event labels to support a low-review release rule.

Machine Learning (cs.LG); Computers and Society (cs.CY)

arXiv:2605.20956 [cs.LG]

(or arXiv:2605.20956v2 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2605.20956 Focus to learn more arXiv-issued DOI via DataCite

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