Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology-Reference-Cited by-同舟云学术

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Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology

Published:2024-05 Issue: Volume: Page:
ISSN:0828-282X
Container-title:Canadian Journal of Cardiology
language:en
Short-container-title:Canadian Journal of Cardiology

Author:

Nolin-Lapalme Alexis,Corbin Denis,Tastet Olivier,Avram Robert,Hussin Julie G.

Funder

Canadian Institute for Advanced Research

Fonds de Recherche du Québec - Santé

Institut de Valorisation des Données

Fonds de recherche du Québec – Nature et technologies

Canadian Institutes of Health Research

Publisher

Elsevier BV

Reference118 articles.

1. Implementing machine learning in interventional cardiology: the benefits are worth the trouble;Ben Ali;Front Cardiovasc Med,2021

2. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare;Feng;NPJ Digit Med,2022

3. Bias in clinical intervention research;Gluud;Am J Epidemiol,2006

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial Intelligence in Cardiovascular Medicine: From Clinical Care, Education, and Research Applications to Foundational Models—A Perspective;Canadian Journal of Cardiology;2024-08

2. A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point of Care: The PACS-AI Platform;Canadian Journal of Cardiology;2024-06

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