Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods

19 May 2023

Raphael Poulain

Mirza Farhan Bin Tarek

Rahmatollah Beheshti

FedML

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Papers citing "Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods"

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Title
AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI Kaveen Hiniduma Suren Byna J. L. Bez Ravi Madduri 98 7 0 27 Jun 2024
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning Trenton Chang Michael Sjoding Jenna Wiens 64 11 0 01 Aug 2022
Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods Ricards Marcinkevics Ece Ozkan Julia E. Vogt 94 18 0 26 Jul 2022
Fair Federated Learning via Bounded Group Loss Shengyuan Hu Zhiwei Steven Wu Virginia Smith FaML FedML 73 15 0 18 Mar 2022
Minimax Demographic Group Fairness in Federated Learning Afroditi Papadaki Natalia Martínez Martín Bertrán Guillermo Sapiro Miguel R. D. Rodrigues FaML FedML 54 46 0 20 Jan 2022
Federated Learning for Smart Healthcare: A Survey Dinh C. Nguyen Quoc-Viet Pham P. Pathirana Ming Ding Aruna Seneviratne Zihuai Lin O. Dobre Won Joo Hwang FedML 83 552 0 16 Nov 2021
Two-step adversarial debiasing with partial learning -- medical image case-studies R. Correa J. Jeong Bhavik Patel Hari M. Trivedi J. Gichoya Imon Banerjee MedIm 48 15 0 16 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 70 36 0 04 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 90 64 0 29 Oct 2021
FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin Shen Yan Chaoyang He Emilio Ferrara A. Avestimehr FedML 90 211 0 02 Oct 2021
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 137 47 0 01 Oct 2021
InfoFair: Information-Theoretic Intersectional Fairness Jian Kang Tiankai Xie Xintao Wu Ross Maciejewski Hanghang Tong FaML 47 20 0 24 May 2021
Mitigating Bias in Federated Learning Annie Abay Yi Zhou Nathalie Baracaldo Shashank Rajamoni Ebube Chuba Heiko Ludwig AI4CE 74 94 0 04 Dec 2020
FairBatch: Batch Selection for Model Fairness Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 87 133 0 03 Dec 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 140 820 0 28 Jul 2020
Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality Pulkit Sharma Farah E. Shamout David Clifton 74 26 0 01 Dec 2019
Federated and Differentially Private Learning for Electronic Health Records Stephen Pfohl Andrew M. Dai Katherine A. Heller OOD FedML 66 51 0 13 Nov 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 150 1,166 0 13 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 578 4,391 0 23 Aug 2019
Counterfactual Reasoning for Fair Clinical Risk Prediction Stephen Pfohl Tony Duan D. Ding N. Shah OOD CML 64 58 0 14 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 174 2,356 0 04 Jul 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms Alekh Agarwal Miroslav Dudík Zhiwei Steven Wu FaML 65 248 0 30 May 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 190 804 0 25 May 2019
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records Li Huang Dianbo Liu OOD FedML 76 370 0 22 Mar 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 139 941 0 01 Feb 2019
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk Stephen Pfohl Ben J. Marafino Adrien Coulet F. Rodriguez L. Palaniappan N. Shah 57 68 0 12 Sep 2018
Adversarial Removal of Demographic Attributes from Text Data Yanai Elazar Yoav Goldberg FaML 113 309 0 20 Aug 2018
Why Is My Classifier Discriminatory? Irene Y. Chen Fredrik D. Johansson David Sontag FaML 71 399 0 30 May 2018
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks Fenglong Ma Radha Chitta Jing Zhou Quanzeng You Tong Sun Jing Gao 60 558 0 19 Jun 2017
Multitask learning and benchmarking with clinical time series data Hrayr Harutyunyan Hrant Khachatrian David C. Kale Greg Ver Steeg Aram Galstyan OOD AI4TS 200 883 0 22 Mar 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 412 17,615 0 17 Feb 2016