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Review Open access Sep 2026

Development and usability testing of a machine learning clinical decision support tool for suggesting etiologies and treatment of clinical deterioration.

BACKGROUND Early warning score clinical decision support (CDS) systems identify patients at risk of clinical deterioration, but do not provide insights on the underlying cause. Machine learning (ML) models may address this limitation, but how to convey such outputs to clinicians remains unclear. This study elicited cli...

Oliver T. Nguyen, Douglas A. Wiegmann, James Haddad et al. · 0 citations
Open access Aug 2026

When nurses are held accountable for AI-driven clinical decisions, they must be engaged early and meaningfully

Abstract Health systems are adopting AI-powered tools faster than policy can address the implications for clinician liability. Nurses, as the largest healthcare profession and the most proximal clinicians to patients, must decide whether to accept, modify, or override AI-derived recommendations, often while managing co...

Meghan Reading Turchioe, A. Wieben, Carolyn Sun et al. · 0 citations

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