Researchers at the University of California San Diego School of Medicine have developed an AI algorithm, COMPOSER, that can predict sepsis in high-risk patients before symptoms occur.

The algorithm continuously monitors over 150 patient variables, like vital signs and lab results, to identify sepsis risk.

In a study involving over 6,000 patient admissions, the use of COMPOSER resulted in a 17% reduction in mortality.

This represents the first improvement in patient outcomes using an AI deep-learning model.

The algorithm is now being used in various hospital in-patient units and will soon be activated at UC San Diego Health's newest location.

The study was funded by the National Institutes of Health and the Joan and Irwin Jacobs Center for Health Innovation at UC San Diego Health.