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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The clinical adoption of artificial intelligence (AI) has focused on enabling automation, but conventional accuracy metrics fail to answer a key question: when is it safe to trust an AI system? We introduce the Safety-Aware Receiver Operating Characteristic (SA-ROC) framework, which defines operational safety as an ability to meet pre-specified reliability levels. The SA-ROC curve delineates a Rule-in and a Rule-out Safe Zone, where autonomous action is permitted, and a Gray Zone, where human review is mandated. To quantify this non-automated workload, we introduce the Gray Zone Area (\u0393\n                    <jats:sub>Area<\/jats:sub>\n                    ), a metric measuring the operational cost of indecision. Our framework reveals a key reversal: in a case study of two FDA-cleared algorithms for cancer screening, the model with a statistically superior AUC was found to be operationally less safe for high-confidence screening. SA-ROC enables active governance, translating clinical policy into optimized workflows that inform operational safety and complement regulatory safety evaluation.\n                  <\/jats:p>","DOI":"10.1038\/s41746-026-02450-7","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T17:17:18Z","timestamp":1771607838000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Defining operational safety in clinical artificial intelligence systems"],"prefix":"10.1038","volume":"9","author":[{"given":"Young-Tak","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyunji","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manisha","family":"Bahl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael H.","family":"Lev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramon Gilberto","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael S.","family":"Gee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Synho","family":"Do","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,20]]},"reference":[{"key":"2450_CR1","doi-asserted-by":"publisher","first-page":"e40238","DOI":"10.2196\/40238","volume":"24","author":"M Sharma","year":"2022","unstructured":"Sharma, M. et al. 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