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Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk

Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk

12 September 2018
Stephen R. Pfohl
Ben J. Marafino
Adrien Coulet
F. Rodriguez
L. Palaniappan
N. Shah
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Papers citing "Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk"

12 / 12 papers shown
Title
Improving Fairness in AI Models on Electronic Health Records: The Case
  for Federated Learning Methods
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods
Raphael Poulain
Mirza Farhan Bin Tarek
Rahmatollah Beheshti
FedML
28
21
0
19 May 2023
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness
Vincent Jeanselme
Maria De-Arteaga
Zhe Zhang
Jessica Barrett
Brian D. M. Tom
FaML
35
11
0
13 Aug 2022
When Personalization Harms: Reconsidering the Use of Group Attributes in
  Prediction
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction
Vinith Suriyakumar
Marzyeh Ghassemi
Berk Ustun
44
6
0
04 Jun 2022
SoFaiR: Single Shot Fair Representation Learning
SoFaiR: Single Shot Fair Representation Learning
Xavier Gitiaux
Huzefa Rangwala
34
4
0
26 Apr 2022
Improving the Fairness of Chest X-ray Classifiers
Improving the Fairness of Chest X-ray Classifiers
Haoran Zhang
Natalie Dullerud
Karsten Roth
Lauren Oakden-Rayner
Stephen R. Pfohl
Marzyeh Ghassemi
23
65
0
23 Mar 2022
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 R. Pfohl
Haoran Zhang
Yizhe Xu
Agata Foryciarz
Marzyeh Ghassemi
N. Shah
OOD
31
22
0
27 Aug 2021
Fair Representations by Compression
Fair Representations by Compression
Xavier Gitiaux
Huzefa Rangwala
FaML
30
14
0
28 May 2021
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal
  Clinical NLP
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
John Chen
Ian Berlot-Attwell
Safwan Hossain
Xindi Wang
Frank Rudzicz
FaML
37
7
0
19 Nov 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk
  Prediction
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction
Stephen R. Pfohl
Agata Foryciarz
N. Shah
FaML
33
108
0
20 Jul 2020
Individual Calibration with Randomized Forecasting
Individual Calibration with Randomized Forecasting
Shengjia Zhao
Tengyu Ma
Stefano Ermon
16
57
0
18 Jun 2020
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
236
676
0
17 Feb 2018
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
207
2,092
0
24 Oct 2016
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