In June 2025, scientific collaborators from Duke AI Health and the American Heart Association, led by principal investigator and former AI Health Director Michael Pencina, PhD, concluded a five-year study funded by the National Institutes of Health and designed to improve the ability to predict a patient’s risk of stroke. After aggregating and harmonizing patient-level data collected from four NIH-sponsored observational cohort studies, the study investigators evaluated the performance of existing stroke risk prediction models, developed new models with the potential to improve clinical decision-making, and explored ways to mitigate algorithmic bias and improve the fairness of models in clinical use. Key findings from the study have been shared through 18 publications in high-impact academic journals and conference proceedings, and the code used to conduct analyses is publicly available through the study’s dedicated GitHub repository.
