Early Prediction of Breast Cancer Recurrence for Patients Treated with Neoadjuvant Chemotherapy: A Transfer Learning Approach on DCE-MRIs

Early Prediction of Breast Cancer Recurrence for Patients Treated with Neoadjuvant Chemotherapy: A Transfer Learning Approach on DCE-MRIs

Cancer treatment planning benefits from an accurate early prediction of the treatment efficacy. The goal of this study is to give an early prediction of three-year Breast Cancer Recurrence (BCR) for patients who underwent neoadjuvant chemotherapy. We addressed the task from a new perspective based o...

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Bibliographic Details
Main Authors: Maria Colomba Comes, Daniele La Forgia, Vittorio Didonna, Annarita Fanizzi, Francesco Giotta, Agnese Latorre, Eugenio Martinelli, Arianna Mencattini, Angelo Virgilio Paradiso, Pasquale Tamborra, Antonella Terenzio, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Cancers
Subjects:
DCE-MRI
neoadjuvant chemotherapy
breast cancer recurrence
Support Vector Machine
convolutional neural networks
transfer learning
Online Access:https://www.mdpi.com/2072-6694/13/10/2298

Internet

https://www.mdpi.com/2072-6694/13/10/2298

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