Technology used by Facebook, Google and Amazon to turn spoken language into text, recognize faces and target advertising could help doctors fight one of the deadliest infections in U.S. hospitals.
Clostridium difficile, a bacterium spread by contact with objects or infected people, thrives in hospitals, causing 453,000 cases a year and 29,000 U.S. deaths, said a 2015 study in the New England Journal of Medicine. Traditional methods such as monitoring hygiene often cannot stop the infection.
But what if it were possible to target those most vulnerable to C. diff? Erica Shenoy, an infectious disease specialist, and Jenna Wiens, a computer scientist and assistant professor of engineering at the University of Michigan, created an algorithm to predict a patient’s risk of developing a C. diff infection, known as CDI, by using patients’ vital signs and other health records. The algorithm — based on a form of artificial intelligence called machine learning — is at the leading edge of a technological wave starting to hit the U.S. health care industry.
Kaiser Health News