When applying artificial intelligence (AI) and machine learning to problems, accuracy is critical. If a model’s predictions aren’t precise, then they can’t contribute to better outcomes, which is vital in the delivery of better care. The objective is for the predictive models to become more accurate through an iterative process. To discuss the evolution of and objectives for iodine AI models, “Iodine Intelligence” Host Hilary Kennedy spoke with Lance Eason, Chief Data Scientist.