Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging

Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging

Abstract Background Artificial intelligence (AI) models are increasingly used in the medical domain. However, as medical data is highly sensitive, special precautions to ensure its protection are required. The gold standard for privacy preservation is the introduction of differential privacy (DP) to...

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Bibliographic Details
Main Authors: Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-024-00462-6

Internet

https://doi.org/10.1038/s43856-024-00462-6

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