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Improving the Fairness of Chest X-ray Classifiers

Improving the Fairness of Chest X-ray Classifiers

23 March 2022
Haoran Zhang
Natalie Dullerud
Karsten Roth
Lauren Oakden-Rayner
Stephen Pfohl
Marzyeh Ghassemi
ArXiv (abs)PDFHTML

Papers citing "Improving the Fairness of Chest X-ray Classifiers"

42 / 42 papers shown
Title
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification
Yicheng Gao
Jinkui Hao
Bo Zhou
125
0
0
20 Dec 2024
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones
Fabio De Sousa Ribeiro
Mélanie Roschewitz
Daniel Coelho De Castro
Ben Glocker
FaMLOODCML
253
2
0
05 Oct 2024
RadFusion: Benchmarking Performance and Fairness for Multimodal
  Pulmonary Embolism Detection from CT and EHR
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR
Yuyin Zhou
Shih-Cheng Huang
Jason Alan Fries
Alaa Youssef
T. Amrhein
...
Imon Banerjee
D. Rubin
Lei Xing
N. Shah
M. Lungren
61
46
0
23 Nov 2021
Simple data balancing achieves competitive worst-group-accuracy
Simple data balancing achieves competitive worst-group-accuracy
Badr Youbi Idrissi
Martín Arjovsky
Mohammad Pezeshki
David Lopez-Paz
115
182
0
27 Oct 2021
A comparison of approaches to improve worst-case predictive model
  performance over patient subpopulations
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations
Stephen Pfohl
Haoran Zhang
Yizhe Xu
Agata Foryciarz
Marzyeh Ghassemi
N. Shah
OOD
62
24
0
27 Aug 2021
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Imon Banerjee
A. Bhimireddy
J. L. Burns
Leo Anthony Celi
Li-Ching Chen
...
Hari M. Trivedi
Ryan Wang
Z. Zaiman
Haoran Zhang
J. Gichoya
70
337
0
21 Jul 2021
Just Train Twice: Improving Group Robustness without Training Group
  Information
Just Train Twice: Improving Group Robustness without Training Group Information
Emmy Liu
Behzad Haghgoo
Annie S. Chen
Aditi Raghunathan
Pang Wei Koh
Shiori Sagawa
Percy Liang
Chelsea Finn
OOD
94
562
0
19 Jul 2021
Fairness On The Ground: Applying Algorithmic Fairness Approaches to
  Production Systems
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems
Chloé Bakalar
Renata Barreto
Stevie Bergman
Miranda Bogen
Bobbie Chern
...
J. Simons
Jonathan Tannen
Edmund Tong
Kate Vredenburgh
Jiejing Zhao
FaML
82
28
0
10 Mar 2021
Does enforcing fairness mitigate biases caused by subpopulation shift?
Does enforcing fairness mitigate biases caused by subpopulation shift?
Subha Maity
Debarghya Mukherjee
Mikhail Yurochkin
Yuekai Sun
131
24
0
06 Nov 2020
Minimax Pareto Fairness: A Multi Objective Perspective
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
74
193
0
03 Nov 2020
Ethical Machine Learning in Health Care
Ethical Machine Learning in Health Care
Irene Y. Chen
Emma Pierson
Sherri Rose
Shalmali Joshi
Kadija Ferryman
Marzyeh Ghassemi
AILaw
74
387
0
22 Sep 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk
  Prediction
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction
Stephen Pfohl
Agata Foryciarz
N. Shah
FaML
71
113
0
20 Jul 2020
Learning from Failure: Training Debiased Classifier from Biased
  Classifier
Learning from Failure: Training Debiased Classifier from Biased Classifier
J. Nam
Hyuntak Cha
SungSoo Ahn
Jaeho Lee
Jinwoo Shin
63
149
0
06 Jul 2020
CheXpert++: Approximating the CheXpert labeler for
  Speed,Differentiability, and Probabilistic Output
CheXpert++: Approximating the CheXpert labeler for Speed,Differentiability, and Probabilistic Output
Matthew B. A. McDermott
T. Hsu
W. Weng
Marzyeh Ghassemi
U. Toronto
72
32
0
26 Jun 2020
Fairness without Demographics through Adversarially Reweighted Learning
Fairness without Demographics through Adversarially Reweighted Learning
Preethi Lahoti
Alex Beutel
Jilin Chen
Kang Lee
Flavien Prost
Nithum Thain
Xuezhi Wang
Ed H. Chi
FaML
121
337
0
23 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaMLFedML
40
40
0
26 May 2020
FairALM: Augmented Lagrangian Method for Training Fair Models with
  Little Regret
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
Vishnu Suresh Lokhande
A. K. Akash
Sathya Ravi
Vikas Singh
FaML
39
31
0
03 Apr 2020
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
H. Zhang
Amy X. Lu
Mohamed Abdalla
Matthew B. A. McDermott
Marzyeh Ghassemi
59
174
0
11 Mar 2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers
CheXclusion: Fairness gaps in deep chest X-ray classifiers
Laleh Seyyed-Kalantari
Guanxiong Liu
Matthew B. A. McDermott
Irene Y. Chen
Marzyeh Ghassemi
OOD
97
293
0
14 Feb 2020
Measurement and Fairness
Measurement and Fairness
Abigail Z. Jacobs
Hanna M. Wallach
78
394
0
11 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
108
1,243
0
20 Nov 2019
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDaFaML
568
4,353
0
23 Aug 2019
Fair Classification and Social Welfare
Fair Classification and Social Welfare
Lily Hu
Yiling Chen
FaML
67
90
0
01 May 2019
Measuring Calibration in Deep Learning
Measuring Calibration in Deep Learning
Jeremy Nixon
Michael W. Dusenberry
Ghassen Jerfel
Timothy Nguyen
Jeremiah Zhe Liu
Linchuan Zhang
Dustin Tran
UQCV
74
489
0
02 Apr 2019
MIMIC-CXR-JPG, a large publicly available database of labeled chest
  radiographs
MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
Alistair E. W. Johnson
Tom Pollard
Nathaniel R. Greenbaum
M. Lungren
Chih-ying Deng
Yifan Peng
Zhiyong Lu
R. Mark
Seth Berkowitz
Steven Horng
MedIm
98
821
0
21 Jan 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and
  Expert Comparison
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Jeremy Irvin
Pranav Rajpurkar
M. Ko
Yifan Yu
Silviana Ciurea-Ilcus
...
D. Larson
C. Langlotz
Bhavik Patel
M. Lungren
A. Ng
112
2,602
0
21 Jan 2019
Learning Controllable Fair Representations
Learning Controllable Fair Representations
Jiaming Song
Pratyusha Kalluri
Aditya Grover
Shengjia Zhao
Stefano Ermon
FaML
59
180
0
11 Dec 2018
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
Stephen Pfohl
Ben J. Marafino
Adrien Coulet
F. Rodriguez
L. Palaniappan
N. Shah
50
67
0
12 Sep 2018
Achieving Fairness through Adversarial Learning: an Application to
  Recidivism Prediction
Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction
C. Wadsworth
Francesca Vera
Chris Piech
FaML
72
180
0
30 Jun 2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
Michael P. Kim
Amirata Ghorbani
James Zou
MLAU
246
343
0
31 May 2018
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
382
684
0
17 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning
Mitigating Unwanted Biases with Adversarial Learning
B. Zhang
Blake Lemoine
Margaret Mitchell
FaML
197
1,390
0
22 Jan 2018
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep
  Learning
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
Pranav Rajpurkar
Jeremy Irvin
Kaylie Zhu
Brandon Yang
Hershel Mehta
...
Aarti Bagul
C. Langlotz
K. Shpanskaya
M. Lungren
A. Ng
LM&MA
83
2,709
0
14 Nov 2017
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup
  Fairness
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
FaML
199
782
0
14 Nov 2017
On Fairness and Calibration
On Fairness and Calibration
Geoff Pleiss
Manish Raghavan
Felix Wu
Jon M. Kleinberg
Kilian Q. Weinberger
FaML
200
880
0
06 Sep 2017
Counterfactual Fairness
Counterfactual Fairness
Matt J. Kusner
Joshua R. Loftus
Chris Russell
Ricardo M. A. Silva
FaML
224
1,584
0
20 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
300
2,120
0
24 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
230
4,329
0
07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
121
1,775
0
19 Sep 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
775
36,861
0
25 Aug 2016
Censoring Representations with an Adversary
Censoring Representations with an Adversary
Harrison Edwards
Amos Storkey
AAMLFaML
66
506
0
18 Nov 2015
The Variational Fair Autoencoder
The Variational Fair Autoencoder
Christos Louizos
Kevin Swersky
Yujia Li
Max Welling
R. Zemel
DRL
223
634
0
03 Nov 2015
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