AI models comb patient data to predict cardiac arrest risk

Researchers have developed artificial intelligence (AI) models that can scrutinize electronic health records (EHR) and electrocardiograms to identify individuals in the general population at elevated risk for sudden cardiac arrest—a condition that causes more than 400,000 U.S. deaths annually and has a survival rate of only 10%. The finding represents a significant advance in predicting a largely unpredictable medical emergency that often strikes people with no known heart disease.