An artificial intelligence (AI) tool had an 88% success rate in predicting life expectancy in patients with heart failure, researchers at UC San Diego Health reported in the European Journal of Heart Failure. Using a machine-learning algorithm, researchers developed a mortality risk score in patients with heart failure. The risk score had an area under the curve of 0.88 and was predictive across the full spectrum of risk, study authors wrote. The results support the use of the AI to evaluate patients with heart failure and in other settings where predicting risk has been challenging, reported the authors. "This tool gives us insight, for example, on the probability that a given patient will die from heart failure in the next three months or a year," said Eric Adler, M.D., cardiologist and director of cardiac transplant and mechanical circulatory support at the Cardiovascular Institute at UC San Diego Health.