2 papers
cs.CY2025
Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
Qiming Wu, Siqi Li, Doudou Zhou +1
Ensuring fairness is critical when applying artificial intelligence to high-stakes domains such as healthcare, where predictive models trained on imbalanced and demographically ske…
cs.CY2024
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction
Siqi Li, Qiming Wu, Xin Li +10
Objective: Mitigating algorithmic disparities is a critical challenge in healthcare research, where ensuring equity and fairness is paramount. While large-scale healthcare data exi…