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Mini WorkShop: Fair Machine Learning for Health Care

Sala A-101-0

The field of Fair Machine Learning attempts to guarantee, in some specific sense, that a machine learning model does not cause harm to a particular subpopulation. Predictive models are increasingly used to support clinical decision making, giving rise to many fairness.
This talk will break down some of the opportunities and
challenges for fair machine learning in health, especially the role of
group-wise calibration and intersectional group definitions.