Prediction Is Not Detection: Evaluating Pre-Recognition Claims in Longitudinal Clinical AI

Abstract:Clinically useful early detection requires validated pre-recognition lead time. Yet event-based evaluations of longitudinal clinical AI can treat recognition-mediated care-process signals as shortcuts and recognition-dependent endpoints as reference standards, inflating apparent performance and lead time while undermining cross-center transport. Such results may serve prognosis without establishing detection before recognition. We define an interval-censored pre-recognition transition, an independent as-of reference standard, and a prespecified recognition proxy to make the claim testable.

Artificial Intelligence (cs.AI)

arXiv:2609.25852 [cs.AI]

(or arXiv:2609.25852v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.25852 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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