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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Detalles Bibliográficos
Autores principales: Ellmann, Stephan, Wenkel, Evelyn, Dietzel, Matthias, Bielowski, Christian, Vesal, Sulaiman, Maier, Andreas, Hammon, Matthias, Janka, Rolf, Fasching, Peter A., Beckmann, Matthias W., Schulz Wendtland, Rüdiger, Uder, Michael, Bäuerle, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992224/
https://www.ncbi.nlm.nih.gov/pubmed/31999755
http://dx.doi.org/10.1371/journal.pone.0228446

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992224/
https://www.ncbi.nlm.nih.gov/pubmed/31999755
http://dx.doi.org/10.1371/journal.pone.0228446

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