University of Texas at Dallas researchers have developed an artificial intelligence tool that could predict the risk of cardiac arrest in children hospitalized in cardiac intensive care units. The technology is the latest work from the Statistical Artificial Intelligence and Relational Learning Group, a UT Dallas research lab where experts develop AI to assist health care providers. Using 11 vital-sign and laboratory variables that were collected from the EHR, combined with historical training/testing sets, the team successfully created a machine-learning predictive algorithm to predict cardiac arrest in children one hour before the cardiac arrest, Natarajan said. The finding tracked with the results of the researchers’ statistical analysis of the data, demonstrating that their algorithm is correct. The pediatric cardiology research was funded by Children’s Health and the ZOLL Foundation.