Social Complexity and Fairness in Synthetic Medical Data

A WASP-HS NetX project examining how machine learning-generated synthetic medical datasets distort representation. Using intersectional analysis, the project developed fairness metrics for synthetic medical data, exploring how intersectionality can contribute to better, more equitable data.