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: ...

Many U.S. hospitals using predictive models are not evaluating their tools internally for accuracy, and fewer still are evaluating them for potential biases, according to a study published in the most ...

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 ...

AI-driven decision tools are increasingly determining what post-acute care services patients receive, and what they don’t. As a health tech CEO working with hospitals, skilled nursing facilities (SNFs ...

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, ...