arXiv Machine Learning September 14, 2026 By Mohammed Sameer Syed, Rozhin Yasaei

Certified AI Triage of ICU Alarms

Read the original on arXiv Machine Learning →

The paper introduces a certified AI triage system for ICU alarms, reframing alarm reduction as a three-way decision (retain, suppress, or defer). It demonstrates that, with a 5% budget, the system can suppress 74.8% of false ventricular‑tachycardia alarms while only silencing 1.5% of genuine ones, achieving an AUROC of 0.953 and a Challenge Score of 83.33—comparable to the best existing methods. The study also explores how grid granularity and calibration affect certification, showing that finer grids can certify fewer alarms but with tighter guarantees.

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