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.  

"Using artificial intelligence applications and health records data, the prediction of cardiac arrest in the general population is feasible,” said Dr. Neal Chatterjee, the study’s lead investigator and a cardiologist at the University of Washington School of Medicine.   

JACC: Advances, a journal of the American College of Cardiology, published the paper today. Other co-senior authors are from Massachusetts General Hospital and the Broad Institute of MIT and Harvard.  

Polycystic ovary syndrome (PCOS), a condition affecting more than 170 million people worldwide, has been officially renamed Polyendocrine Metabolic Ovarian Syndrome (PMOS) following a landmark global consensus study published today in The Lancet.

A new UC Irvine study uses monetized life-cycle analysis to compare hydrogen, direct electrification and fossil fuel pathways across heavy-duty transport and industrial sectors. The researchers concluded that renewable hydrogen applied in certain sectors offers greater social value, which includes reduced climate change impacts, cleaner air, improved public health and lower demand for natural resources. The researchers pinpointed steel, transoceanic shipping and long-haul trucking as the highest-value targets for clean hydrogen deployment.