Artificial Intelligence examining ECGs predicts irregular heartbeat, death risk

Artificial intelligence can examine electrocardiogram (ECG) test results, a common medical test, to pinpoint patients at higher risk of developing a potentially dangerous irregular heartbeat (arrhythmia) or of dying within the next year, according to two preliminary studies to be presented at the American Heart Association's Scientific Sessions 2019--November 16-18 in Philadelphia. Researchers used more than 2 million ECG results from more than three decades of archived medical records in Pennsylvania/New Jersey's Geisinger Health System to train deep neural networks--advanced, multi-layered computational structures. Both studies, from the same group of researchers, are among the first to use artificial intelligence to predict future events from an ECG rather than to detect current health problems, the scientists noted. "This is exciting and provides more evidence that we are on the verge of a revolution in medicine where computers will be working alongside physicians to improve patient care," said Brandon Fornwalt, M.D., Ph.D., senior author on both studies and associate professor and chair of the Department of Imaging Science and Innovation at Geisinger in Danville, Pennsylvania. Researchers speculated that a deep learning model could predict irregular heart rhythms, known as atrial fibrillation (AF), before it develops.