Pharmacy Times January 26, 2022
A machine-learning method called XGBoost provided the highest overall accuracy, despite being the least complex model.
Several common machine learning algorithms could accurately predict which hospitalized patients will become infected with C. difficile, according to new research published in the American Journal of Infection Control.
The study authors said the findings could support prevention and early diagnosis of infections, as well as more timely implementation of infection control measures to minimize spread. C. diff is the leading cause of hospital-acquired diarrhea and is associated with significant morbidity, mortality, and health care costs, but despite these problems there is currently no gold standard tool to assess individual patients’ risk of infection.
“Our study findings suggest that [machine learning algorithms] could play...