tutorial

Fairness in Machine Learning for Healthcare

Authors:

Muhammad Aurangzeb Ahmad,

Arpit Patel,

Carly Eckert,

Vikas Kumar,

Ankur TeredesaiAuthors Info & Claims

KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Pages 3529 - 3530

https://doi.org/10.1145/3394486.3406461

Published: 20 August 2020 Publication History

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Abstract

The issue of bias and fairness in healthcare has been around for centuries. With the integration of AI in healthcare the potential to discriminate and perpetuate unfair and biased practices in healthcare increases many folds The tutorial focuses on the challenges, requirements and opportunities in the area of fairness in healthcare AI and the various nuances associated with it. The problem healthcare as a multi-faceted systems level problem that necessitates careful of different notions of fairness in healthcare to corresponding concepts in machine learning is elucidated via different real world examples.

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Chaturvedi UChauhan SSingh I(2025)The Impact of Artificial Intelligence on Remote Healthcare: Enhancing Patient Engagement, Connectivity, and Overcoming ChallengesIntelligent Pharmacy10.1016/j.ipha.2024.12.003Online publication date: Jan-2025
https://doi.org/10.1016/j.ipha.2024.12.003
Miller TDurlik IŁobodzińska ADorobczyński LJasionowski R(2024)AI in Context: Harnessing Domain Knowledge for Smarter Machine LearningApplied Sciences10.3390/app14241161214:24(11612)Online publication date: 12-Dec-2024
https://doi.org/10.3390/app142411612
Kumar ASinghal KKushwah K(2024)Healthcare Machine Learning InsightsPrediction in Medicine: The Impact of Machine Learning on Healthcare10.2174/9789815305128124010014(219-231)Online publication date: 10-Oct-2024
https://doi.org/10.2174/9789815305128124010014
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Index Terms

Fairness in Machine Learning for Healthcare
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
    2. Health informatics
2. Computing methodologies
  1. Artificial intelligence
  2. Machine learning
    1. Machine learning algorithms

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Published In

KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

August 2020

3664 pages

ISBN:9781450379984

DOI:10.1145/3394486

General Chairs:
Rajesh Gupta
UC San Diego, USA
,
Yan Liu
USC, USA
,
Program Chairs:
Mohak Shah
LG Electronics, USA
,
Suju Rajan
Linkedin, USA
,
Publications Chairs:
Jiliang Tang
Michigan State, USA
,
B. Aditya Prakash
Georgia Tech, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 20 August 2020

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KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

July 6 - 10, 2020

CA, Virtual Event, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Chaturvedi UChauhan SSingh I(2025)The Impact of Artificial Intelligence on Remote Healthcare: Enhancing Patient Engagement, Connectivity, and Overcoming ChallengesIntelligent Pharmacy10.1016/j.ipha.2024.12.003Online publication date: Jan-2025
https://doi.org/10.1016/j.ipha.2024.12.003
Miller TDurlik IŁobodzińska ADorobczyński LJasionowski R(2024)AI in Context: Harnessing Domain Knowledge for Smarter Machine LearningApplied Sciences10.3390/app14241161214:24(11612)Online publication date: 12-Dec-2024
https://doi.org/10.3390/app142411612
Kumar ASinghal KKushwah K(2024)Healthcare Machine Learning InsightsPrediction in Medicine: The Impact of Machine Learning on Healthcare10.2174/9789815305128124010014(219-231)Online publication date: 10-Oct-2024
https://doi.org/10.2174/9789815305128124010014
Mishra S(2024)Growing Importance of Machine Learning in Healthcare to Determine Potential RiskPrediction in Medicine: The Impact of Machine Learning on Healthcare10.2174/9789815305128124010011(136-158)Online publication date: 10-Oct-2024
https://doi.org/10.2174/9789815305128124010011
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Li YZhang JZhao YChen BYu S(2024)Fairness-Aware Federated Learning Framework on Heterogeneous Data DistributionsICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10623037(728-733)Online publication date: 9-Jun-2024
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