AI & ML Practical Magic

New math can spot life-threatening internal bleeding in patients before doctors can even see it.

March 24, 2026

Original Paper

Identification of physiological shock in intensive care units via Bayesian regime switching models

Emmett B. Kendall, Jonathan P. Williams, Curtis B. Storlie, Misty A. Radosevich, Erica D. Wittwer, Matthew A. Warner

arXiv · 2603.22208

The Takeaway

Internal bleeding is a 'silent killer' in intensive care units because it remains hidden until a patient's body suddenly fails. This algorithm monitors vital signs to spot the subtle 'invisible' shifts into shock, providing a critical early warning that human observation alone often misses.

From the abstract

Detection of occult hemorrhage (i.e., internal bleeding) in patients in intensive care units (ICUs) can pose significant challenges for critical care workers. Because blood loss may not always be clinically apparent, clinicians rely on monitoring vital signs for specific trends indicative of a hemorrhage event. The inherent difficulties of diagnosing such an event can lead to late intervention by clinicians which has catastrophic consequences. Therefore, a methodology for early detection of hemo