Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer

Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer

Abstract For endocrine-positive Her2 negative breast cancer patients at an early stage, the benefit of adding chemotherapy to adjuvant endocrine therapy is not still confirmed. Several genomic tests are available on the market but are very expensive. Therefore, there is the urgent need to explore no...

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Bibliographic Details
Main Authors: Annarita Fanizzi, Domenico Pomarico, Alessandro Rizzo, Samantha Bove, Maria Colomba Comes, Vittorio Didonna, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Nicole Petruzzellis, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Format: Article
Language:English
Published: Nature Portfolio 2023-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-35344-9

Internet

https://doi.org/10.1038/s41598-023-35344-9

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