Analyzing breast cancer invasive disease event classification through explainable artificial intelligence

Analyzing breast cancer invasive disease event classification through explainable artificial intelligence

IntroductionRecently, accurate machine learning and deep learning approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral and second cancers. However, such approaches are poorly interpretable.MethodsThus, we designed an E...

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Bibliographic Details
Main Authors: Raffaella Massafra, Annarita Fanizzi, Nicola Amoroso, Samantha Bove, Maria Colomba Comes, Domenico Pomarico, Vittorio Didonna, Sergio Diotaiuti, Luisa Galati, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Angela Lombardi, Annalisa Nardone, Maria Irene Pastena, Cosmo Maurizio Ressa, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Angelo Virgilio Paradiso, Roberto Bellotti, Vito Lorusso
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Medicine
Subjects:
invasive disease events
breast cancer
explainable AI
10-year follow up
5-year follow up
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1116354/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2023.1116354/full

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