Algorithmic Fairness in Healthcare Data with Weighted Loss and Adversarial Learning

Author:

Das Pronaya Prosun,Mast Marcel,Wiese Lena,Jack Thomas,Wulff Antje,

Publisher

Springer Nature Switzerland

Reference33 articles.

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2. Barocas, S., Hardt, M., Narayanan, A.: Fairness and machine learning. fairmlbook (2019). www.fairmlbook.org

3. Beutel, A., Chen, J., Zhao, Z., Chi, Ed.H..: Data decisions and theoretical implications when adversarially learning fair representations (2017). arXiv:1707.00075

4. Bone, R.C., Balk, R.A., Cerra, F.B., Dellinger, R.P., Fein, A.M., Knaus, W.A., Schein, R.M.H., Sibbald, W.J.: Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Chest 101(6), 1644–1655 (1992)

5. Char, D.S., Shah, N.H., Magnus, D.: Implementing machine learning in health care-addressing ethical challenges. New England J. Med. 378(11), 981 (2018)

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