Fairness in Machine Learning for Healthcare

Author:

Ahmad Muhammad Aurangzeb1,Patel Arpit2,Eckert Carly2,Kumar Vikas3,Teredesai Ankur4

Affiliation:

1. University of Washington Tacoma, Seattle, WA, USA

2. University of Washington, Seattle, WA, USA

3. KenSci Inc., Seattle, WA, USA

4. University of Washington Tacoma & KenSci Inc, Seattle, WA, USA

Publisher

ACM

Cited by 37 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The limits of fair medical imaging AI in real-world generalization;Nature Medicine;2024-06-28

2. Fairness-Aware Federated Learning Framework on Heterogeneous Data Distributions;ICC 2024 - IEEE International Conference on Communications;2024-06-09

3. Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training;European Interdisciplinary Cybersecurity Conference;2024-06-05

4. Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

5. Emotion AI Use in U.S. Mental Healthcare: Potentially Unjust and Techno-Solutionist;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

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