Business leaders today are navigating an era of complex uncertainty, where risk moves faster than traditional oversight can keep up. From global supply chain volatility to internal compliance ...

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: ...

AI has become an increasingly hot technology for the healthcare sector, boosting venture capital investment and spurring interest in tools that could stretch the overburdened provider workforce. But ...

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, ...

Predictive models are used across the student life cycle in higher education, to gauge yield in admissions as well as retention and graduation initiatives, as campus leaders look to understand what ...