Fair Machine Learning in Healthcare: A Review

29 June 2022

Papers citing "Fair Machine Learning in Healthcare: A Review"

9 / 9 papers shown

Title
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 66 44 0 01 Oct 2021
Fairness guarantee in multi-class classification Christophe Denis Romuald Elie Mohamed Hebiri Franccois Hu FaML 28 47 0 28 Sep 2021
On the Fairness of Swarm Learning in Skin Lesion Classification Dian Fan Yifan Wu Xiaoxiao Li 35 19 0 24 Sep 2021
Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? M. Kuppler Christoph Kern Ruben L. Bach Frauke Kreuter FaML 17 19 0 04 May 2021
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary Jean-Francois Rajotte S. Mukherjee Caleb Robinson Anthony Ortiz Christopher West J. L. Ferres R. Ng FedML MedIm 122 40 0 18 Jan 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,143 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 210 669 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,079 0 24 Oct 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,150 0 09 Jun 2011