Shortcut learning leads to sex bias in deep learning models for photoacoustic tomography

Shortcut learning has been identified as a source of algorithmic unfairness in medical imaging artificial intelligence (AI), but its impact on photoacoustic tomography (PAT), particularly concerning sex bias, remains underexplored. This study investigates this issue using peripheral artery disease (...

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Main Authors: Knopp, Marcel (Author) , Bender, Christoph J. (Author) , Holzwarth, Niklas (Author) , Li, Yi (Author) , Kempf, Julius (Author) , Caranovic, Milenko (Author) , Knieling, Ferdinand (Author) , Lang, Werner (Author) , Rother, Ulrich (Author) , Seitel, Alexander (Author) , Maier-Hein, Lena (Author) , Dreher, Kris (Author)
Format: Article (Journal)
Language:English
Published: July 2025
In: International journal of computer assisted radiology and surgery
Year: 2025, Volume: 20, Issue: 7, Pages: 1325-1333
ISSN:1861-6429
DOI:10.1007/s11548-025-03370-9
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s11548-025-03370-9
Verlag, lizenzpflichtig, Volltext: https://link.springer.com/article/10.1007/s11548-025-03370-9
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Author Notes:Marcel Knopp, Christoph J. Bender, Niklas Holzwarth, Yi Li, Julius Kempf, Milenko Caranovic, Ferdinand Knieling, Werner Lang, Ulrich Rother, Alexander Seitel, Lena Maier-Hein, Kris K. Dreher
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Summary:Shortcut learning has been identified as a source of algorithmic unfairness in medical imaging artificial intelligence (AI), but its impact on photoacoustic tomography (PAT), particularly concerning sex bias, remains underexplored. This study investigates this issue using peripheral artery disease (PAD) diagnosis as a specific clinical application.
Item Description:Online verfügbar: 09. Mai 2025
Gesehen am 23.10.2025
Physical Description:Online Resource
ISSN:1861-6429
DOI:10.1007/s11548-025-03370-9