When Clinical Judgment Becomes a Predictive Shortcut: Two Questions Clinical AI Must Answer Before Deployment (arxiv.org)
arXiv:2609.25852v2 Announce Type: replace
Abstract: Clinical AI can predict outcomes using information generated by existing clinical judgment. Such performance alone cannot establish usefulness before recognition or across care processes. We propose evidence requirements matched to intended use and information conditions, with additional state-reference and proxy-relative timing tests for stronger recognition claims. This framework helps hospitals assess whether the conditions supporting performance hold when assistance is most needed. These questions remain outside current evaluation practice leakage checks, overall predictive performance, and external validation do not address them; the framework makes them explicit and specifies the direct evidence required to answer them.
Abstract: Clinical AI can predict outcomes using information generated by existing clinical judgment. Such performance alone cannot establish usefulness before recognition or across care processes. We propose evidence requirements matched to intended use and information conditions, with additional state-reference and proxy-relative timing tests for stronger recognition claims. This framework helps hospitals assess whether the conditions supporting performance hold when assistance is most needed. These questions remain outside current evaluation practice leakage checks, overall predictive performance, and external validation do not address them; the framework makes them explicit and specifies the direct evidence required to answer them.
Comments