Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation

Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation

BackgroundArtificial intelligence (AI) techniques have been proposed for automation of cine CMR segmentation for functional quantification. However, in other applications AI models have been shown to have potential for sex and/or racial bias. The objective of this paper is to perform the first analy...

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Bibliographic Details
Main Authors: Esther Puyol-Antón, Bram Ruijsink, Jorge Mariscal Harana, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Reza Razavi, Phil Chowienczyk, Andrew P. King
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
cardiac magnetic resonance
deep learning
fair AI
segmentation
inequality fairness in deep learning-based CMR segmentation
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2022.859310/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2022.859310/full

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