Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, ...

This study compared 6 algorithmic fairness–improving approaches for low-birth-weight predictive models and found that they improved accuracy but decreased sensitivity for Black populations. Objective: ...

Health systems rely on commercial prediction algorithms to identify and help patients with complex health needs. We show that a widely used algorithm, typical of this industry-wide approach and ...

Algorithms have a critical role to play in population health management. Through a collective process of ensuring that these algorithms are constructed and applied fairly, we can ensure these benefits ...

Only 61% of hospitals using AI or a predictive model report evaluating for accuracy using local data, and just 44% do so for bias, according to a recent study. Analyses suggest that hospitals with ...

Around the world, algorithms are increasingly being asked to do something once reserved for human judgment: help decide who should remain free and who should be deprived of liberty. In recent years, ...