Counterpart Fairness--Addressing Systematic between-group Differences in Fairness Evaluation
We analyzed the impact of systematic differences and biases in data collection on group fairness assessment and accordingly proposed a counterpart-based fairness evaluation index.
Nov 19, 2024
Assessing fairness in machine learning models: A study of racial bias using matched counterparts in mortality prediction for patients with chronic diseases
This study contributes to research on fairness assessment by focusing on the examination of systematic disparities and underscores the potential for revealing racial bias in machine learning models used in clinical settings.
Jun 11, 2024
Oral Presentation at AMIA 2023 Annual Symposium
In Session 14: Application of Informatics in Health Equity - "All the Things You Are" at AMIA.
Nov 13, 2023
On dyadic fairness: Exploring and mitigating bias in graph connections.
We theoretically relate the graph connections to dyadic fairness on link predictive scores in learning graph neural networks and accordingly introduced an algorithm for fair link prediction by adjusting the adjacency weight matrix to address the fairness-utility trade-off.
Jan 12, 2021