Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging
Abstract Background Over the next 5 years, new breast cancer screening guidelines recommending magnetic resonance imaging (MRI) for certain patients will significantly increase the volume of imaging data to be analyzed. While this increase poses challenges for radiologists, artificial intelligence (...
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| Main Authors: | Oliver Lester Saldanha, Jiefu Zhu, Gustav Müller-Franzes, Zunamys I. Carrero, Nicholas R. Payne, Lorena Escudero Sánchez, Paul Christophe Varoutas, Sreenath Kyathanahally, Narmin Ghaffari Laleh, Kevin Pfeiffer, Marta Ligero, Jakob Behner, Kamarul A. Abdullah, Georgios Apostolakos, Chrysafoula Kolofousi, Antri Kleanthous, Michail Kalogeropoulos, Cristina Rossi, Sylwia Nowakowska, Alexandra Athanasiou, Raquel Perez-Lopez, Ritse Mann, Wouter Veldhuis, Julia Camps, Volkmar Schulz, Markus Wenzel, Sergey Morozov, Alexander Ciritsis, Christiane Kuhl, Fiona J. Gilbert, Daniel Truhn, Jakob Nikolas Kather |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-024-00722-5 |
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