A team of Duke Health data scientists, clinicians, administration leadership, and researchers trained three AI models on thousands of surgical cases as part of a recent study focused on usefulness of algorithms. The findings could help streamline the use of one of the most expensive resources in a hospital setting — operating rooms.
“One of the most remarkable things about this finding is that we’ve been able to apply it immediately and connect patients with the surgical care they need more quickly,” said Daniel Buckland M.D., Ph.D., corresponding author and assistant professor in the Department of Emergency Medicine and Department of Surgery at Duke University School of Medicine.
According to the article, machine-learning algorithms are 13% more accurate in predicting the surgical time needed in the operating room compared with human schedulers.
Read the full article here.