Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses.

Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses.

We investigated whether the integration of machine learning (ML) into MRI interpretation can provide accurate decision rules for the management of suspicious breast masses. A total of 173 consecutive patients with suspicious breast masses upon complementary assessment (BI-RADS IV/V: n = 100/76) rece...

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Bibliographic Details
Main Authors: Stephan Ellmann, Evelyn Wenkel, Matthias Dietzel, Christian Bielowski, Sulaiman Vesal, Andreas Maier, Matthias Hammon, Rolf Janka, Peter A Fasching, Matthias W Beckmann, Rüdiger Schulz Wendtland, Michael Uder, Tobias Bäuerle
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0228446

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https://doi.org/10.1371/journal.pone.0228446

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