A machine-learning algorithm has the capability to identify hospitalized patients at risk for severe sepsis and septic shock using data from electronic health records (EHRs), according to a study ...

Geisinger and IBM this week announced this week that they've co-created a new predictive model to help clinicians flag sepsis risk using data from the integrated health system's electronic health ...

FORT DETRICK, Md. – A new invention developed at the U.S. Army Medical Research and Development Command uses an artificial intelligence machine learning algorithm to identify whether burn patients are ...

A proposed artificial intelligence tool to support clinician decision-making about hospital patients at risk for sepsis has an unusual feature: accounting for its lack of certainty and suggesting what ...